Semantic Web meets Integrative Biology: a survey
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paper_title: e-Neuroscience: challenges and triumphs in integrating distributed data from molecules to brains

paper_content:

Imaging, from magnetic resonance imaging (MRI) to localization of specific macromolecules by microscopies, has been one of the driving forces behind neuroinformatics efforts of the past decade. Many web-accessible resources have been created, ranging from simple data collections to highly structured databases. Although many challenges remain in adapting neuroscience to the new electronic forum envisioned by neuroinformatics proponents, these efforts have succeeded in formalizing the requirements for effective data sharing and data integration across multiple sources. In this perspective, we discuss the importance of spatial systems and ontologies for proper modeling of neuroscience data and their use in a large-scale data integration effort, the Biomedical Informatics Research Network (BIRN).
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paper_title: Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL

paper_content:

Semantic Web models and technologies provide information in machine-readable languages that enable computers to access the Web more intelligently and perform tasks automatically without the direction of users. These technologies are relatively recent and advancing rapidly, creating a set of unique challenges for those developing applications. ::: ::: Semantic Web for the Working Ontologist is the essential, comprehensive resource on semantic modeling, for practitioners in health care, artificial intelligence, finance, engineering, military intelligence, enterprise architecture, and more. Focused on developing useful and reusable models, this market-leading book explains how to build semantic content (ontologies) and how to build applications that access that content. ::: ::: New in this edition: ::: ::: ::: Coverage of the latest Semantic Web tools for organizing, querying, and processing information - see details in TOC below ::: ::: Detailed information on the latest ontologies used in key web applications including ecommerce, social networking, data mining, using government data, and more ::: ::: ::: ::: ::: Updated with the latest developments and advances in Semantic Web technologies for organizing, querying, and processing information, including SPARQL, RDF and RDFS, OWL 2.0, and SKOS ::: Detailed information on the ontologies used in today's key web applications, including ecommerce, social networking, data mining, using government data, and more ::: Even more illustrative examples and case studies that demonstrate what semantic technologies are and how they work together to solve real-world problems ::: ::: Table of Contents ::: ::: 1?What Is The Semantic Web? ::: 2?Semantic Modeling ::: 3?RDF - The Basis of the Semantic Web ::: 4?SPARQL - The Query Language for RDF ::: 5?Semantic Web Application Architecture ::: 6?RDF And Inferencing ::: 7?RDF Schema Language ::: 8?RDFS-Plus ::: 9?SKOS - the Simple Knowledge Organization System ::: 10?Ontologies in the Wild: Linked Open Data and the Open Graph Project ::: 11?Basic OWL ::: 12?Counting and Sets In OWL ::: 13?MORE Ontologies in the Wild: QUDT, GoodRelations, and OBO Foundry ::: 14?Good and Bad Modeling Practices ::: 15?OWL 2.0 Levels and Logic ::: 16?Conclusions ::: 17?Frequently Asked Questions
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paper_title: Structuring the Life Science Resourceome for Semantic Systems Biology: Lessons from the BioGateway Project

paper_content:

The application of Semantic Web technologies in the life sci- ences for data integration is still nascent. We have recently built Bio- Gateway, an RDF store that integrates all the candidate OBO Foundry ontologies with other resources such as SWISS-PROT. In the course of developing BioGateway, we faced challenges that are common to other projects that involve large datasets in diverse formats. We present a detailed analysis of the obstacles that had to be solved in creating Bio- Gateway. In doing so, we demonstrate the potential of a comprehensive application of Semantic Web technologies to global biomedical data. The time is ripe for launching a community effort aiming at a wider accep- tance and application of Semantic Web technologies in the life sciences domain. We make a public call for the creation of a forum that strives to implement a truly semantic life science foundation of a type of Systems Biology that we named Semantic Systems Biology.
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paper_title: Taverna: a tool for building and running workflows of services

paper_content:

Taverna is an application that eases the use and integration of the growing number of molecular biology tools and databases available on the web, especially web services. It allows bioinformaticians to construct workflows or pipelines of services to perform a range of different analyses, such as sequence analysis and genome annotation. These high-level workflows can integrate many different resources into a single analysis. Taverna is available freely under the terms of the GNU Lesser General Public License (LGPL) from http://taverna.sourceforge.net/.
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paper_title: The Semantic Web Revisited

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The article included many scenarios in which intelligent agents and bots undertook tasks on behalf of their human or corporate owners. Of course, shopbots and auction bots abound on the Web, but these are essentially handcrafted for particular tasks: they have little ability to interact with heterogeneous data and information types. Because we haven't yet delivered large-scale, agent-based mediation, some commentators argue that the semantic Web has failed to deliver. We argue that agents can only flourish when standards are well established and that the Web standards for expressing shared meaning have progressed steadily over the past five years
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paper_title: Bio-ontologies: current trends and future directions

paper_content:

In recent years, as a knowledge-based discipline, bioinformatics has been made more computationally amenable. After its beginnings as a technology advocated by computer scientists to overcome problems of heterogeneity, ontology has been taken up by biologists themselves as a means to consistently annotate features from genotype to phenotype. In medical informatics, artifacts called ontologies have been used for a longer period of time to produce controlled lexicons for coding schemes. In this article, we review the current position in ontologies and how they have become institutionalized within biomedicine. As the field has matured, the much older philosophical aspects of ontology have come into play. With this and the institutionalization of ontology has come greater formality. We review this trend and what benefits it might bring to ontologies and their use within biomedicine.
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paper_title: YeastHub : a semantic web use case for integrating data in the life sciences domain

paper_content:

Motivation: As the semantic web technology is maturing and the need for life sciences data integration over the web is growing, it is important to explore how data integration needs can be addressed by the semantic web. The main problem that we face in data integration is a lack of widely-accepted standards for expressing the syntax and semantics of the data. We address this problem by exploring the use of semantic web technologies---including resource description framework (RDF), RDF site summary (RSS), relational-database-to-RDF mapping (D2RQ) and native RDF data repository---to represent, store and query both metadata and data across life sciences datasets. ::: ::: Results: As many biological datasets are presently available in tabular format, we introduce an RDF structure into which they can be converted. Also, we develop a prototype web-based application called YeastHub that demonstrates how a life sciences data warehouse can be built using a native RDF data store (Sesame). This data warehouse allows integration of different types of yeast genome data provided by different resources in different formats including the tabular and RDF formats. Once the data are loaded into the data warehouse, RDF-based queries can be formulated to retrieve and query the data in an integrated fashion. ::: ::: Availability: The YeastHub website is accessible via the following URL: http://yeasthub.gersteinlab.org ::: ::: Contact: kei.cheung@yale.edu
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paper_title: Systems Biology, Integrative Biology, Predictive Biology

paper_content:

The pursuit of science is based on empiricism enabled by advancing technologies. Theories then emerge that unify our understanding of natural order. The trinity of experimentation, theory, and technology that underlies the scientific method cannot be placed into a hierarchy of importance. Theoretical fields quickly lose substance in the absence of robust experimentation, and theoretical conundrums cannot be resolved without experimentation using advanced technologies.
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paper_title: A translation approach to portable ontology specifications

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Abstract To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse—definitions of classes, relations, functions, and other objects—is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems. Definitions written in a standard format for predicate calculus are translated by a system called Ontolingua into specialized representations, including frame-based systems as well as relational languages. This allows researchers to share and reuse ontologies, while retaining the computational benefits of specialized implementations. We discuss how the translation approach to portability addresses several technical problems. One problem is how to accommodate the stylistic and organizational differences among representations while preserving declarative content. Another is how to translate from a very expressive language into restricted languages, remaining system-independent while preserving the computational efficiency of implemented systems. We describe how these problems are addressed by basing Ontolingua itself on an ontology of domain-independent, representational idioms.
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paper_title: Biological knowledge management: the emerging role of the Semantic Web technologies

paper_content:

New knowledge is produced at a continuously increasing speed, and the list of papers, databases and other knowledge sources that a researcher in the life sciences needs to cope with is actually turning into a problem rather than an asset. The adequate management of knowledge is therefore becoming fundamentally important for life scientists, especially if they work with approaches that thoroughly depend on knowledge integration, such as systems biology. Several initiatives to organize biological knowledge sources into a readily exploitable resourceome are presently being carried out. Ontologies and Semantic Web technologies revolutionize these efforts. Here, we review the benefits, trends, current possibilities, and the potential this holds for the biosciences.
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paper_title: Knowledge sharing and collaboration in translational research, and the DC-THERA Directory

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Biomedical research relies increasingly on large collections of data sets and knowledge whose generation, representation and analysis often require large collaborative and interdisciplinary efforts. This dimension of ‘big data’ research calls for the development of computational tools to manage such a vast amount of data, as well as tools that can improve communication and access to information from collaborating researchers and from the wider community. Whenever research projects have a defined temporal scope, an additional issue of data management arises, namely how the knowledge generated within the project can be made available beyond its boundaries and life-time. DC-THERA is a European ‘Network of Excellence’ (NoE) that spawned a very large collaborative and interdisciplinary research community, focusing on the development of novel immunotherapies derived from fundamental research in dendritic cell immunobiology. In this article we introduce the DC-THERA Directory, which is an information system designed to support knowledge management for this research community and beyond. We present how the use of metadata and Semantic Web technologies can effectively help to organize the knowledge generated by modern collaborative research, how these technologies can enable effective data management solutions during and beyond the project lifecycle, and how resources such as the DC-THERA Directory fit into the larger context of e-science.
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paper_title: Interdisciplinary integration in Europe: the case of the Fifth Framework programme

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Abstract This paper describes an investigation into the experience of researchers and research managers involved in the European Union Fifth Framework Programme (FP5) with its ambitious encouragement of more integrated problem-oriented approaches to research. We used a series of workshops, a questionnaire survey, individual telephone interviews and six detailed case studies to examine the extent to which these ambitions for ‘interdisciplinary integration’ were being met and the issues involved. Various models of disciplinary integration were identified, which may be appropriate in particular settings. Whilst we found disappointingly few projects that seemed by our criteria to be clearly interdisciplinary, particularly in crossing the boundary between natural and social sciences, we did find a great deal of learning taking place about how to conduct interdisciplinary research and how to overcome some of the difficulties experienced. Researchers emphasised in particular the importance of careful consortium development and team building as a basis for effective interdisciplinary research, and the time and effort needed to establish effective communication between different specialisms. The paper identifies barriers to collaboration between disciplines and some strategies and measures through which closer integration, and its associated benefits, might best be secured.
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paper_title: A Framework for Web Science

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This text sets out a series of approaches to the analysis and synthesis of the World Wide Web, and other web-like information structures. A comprehensive set of research questions is outlined, together with a sub-disciplinary breakdown, emphasising the multi-faceted nature of the Web, and the multi-disciplinary nature of its study and development. These questions and approaches together set out an agenda for Web Science, the science of decentralised information systems. Web Science is required both as a way to understand the Web, and as a way to focus its development on key communicational and representational requirements. The text surveys central engineering issues, such as the development of the Semantic Web, Web services and P2P. Analytic approaches to discover the Web's topology, or its graph-like structures, are examined. Finally, the Web as a technology is essentially socially embedded; therefore various issues and requirements for Web use and governance are also reviewed.
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paper_title: Towards a cyberinfrastructure for the biological sciences: progress, visions and challenges

paper_content:

Biology is an information-driven science. Large-scale data sets from genomics, physiology, population genetics and imaging are driving research at a dizzying rate. Simultaneously, interdisciplinary collaborations among experimental biologists, theorists, statisticians and computer scientists have become the key to making effective use of these data sets. However, too many biologists have trouble accessing and using these electronic data sets and tools effectively. A 'cyberinfrastructure' is a combination of databases, network protocols and computational services that brings people, information and computational tools together to perform science in this information-driven world. This article reviews the components of a biological cyberinfrastructure, discusses current and pending implementations, and notes the many challenges that lie ahead.
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paper_title: Integrating biological databases

paper_content:

Recent years have seen an explosion in the amount of available biological data. More and more genomes are being sequenced and annotated, and protein and gene interaction data are accumulating. Biological databases have been invaluable for managing these data and for making them accessible. Depending on the data that they contain, the databases fulfil different functions. But, although they are architecturally similar, so far their integration has proved problematic.
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paper_title: The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration

paper_content:

The value of any kind of data is greatly enhanced when it exists in a form that allows it to be integrated with other data. One approach to integration is through the annotation of multiple bodies of data using common controlled vocabularies or 'ontologies'. Unfortunately, the very success of this approach has led to a proliferation of ontologies, which itself creates obstacles to integration. The Open Biomedical Ontologies (OBO) consortium is pursuing a strategy to overcome this problem. Existing OBO ontologies, including the Gene Ontology, are undergoing coordinated reform, and new ontologies are being created on the basis of an evolving set of shared principles governing ontology development. The result is an expanding family of ontologies designed to be interoperable and logically well formed and to incorporate accurate representations of biological reality. We describe this OBO Foundry initiative and provide guidelines for those who might wish to become involved.
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paper_title: Will Widgets and Semantic Tagging Change Computational Biology?

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We argue here, through the use of several examples from our work in support of structural biology, that the answer to the question posed by the title of this Perspective is a resounding yes. The discussion that follows is aimed primarily at those of the journal's readers who are biological resource developers and Web page developers interested in developing the richest possible Web pages. However, those of you who simply use biological resources might find this a helpful discussion in understanding what is on the horizon. Whatever your interest, please let us hear your opinion on the question posed by this Perspective through the associated comment feature.
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paper_title: Linking Open Drug Data

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The development of new therapies for diseases requires the integration of large amounts of biomedical data from many different sources. The goal of the Linking Open Drug Data (LODD) project is to facilitate this integration by bringing these data sources onto the Web of Linked Data. We describe the different datasets published by this project, which are strongly interlinked with other Linked Data sources and contain 8.4 million RDF triples. A use case is provided that demonstrates the benefit of this work to patients and medical researchers.
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paper_title: Linked Data: Evolving the Web Into a Global Data Space

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The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study.
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paper_title: Semantic web data warehousing for caGrid

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The National Cancer Institute (NCI) is developing caGrid as a means for sharing cancer-related data and services. As more data sets become available on caGrid, we need effective ways of accessing and integrating this information. Although the data models exposed on caGrid are semantically well annotated, it is currently up to the caGrid client to infer relationships between the different models and their classes. In this paper, we present a Semantic Web-based data warehouse (Corvus) for creating relationships among caGrid models. This is accomplished through the transformation of semantically-annotated caBIG® Unified Modeling Language (UML) information models into Web Ontology Language (OWL) ontologies that preserve those semantics. We demonstrate the validity of the approach by Semantic Extraction, Transformation and Loading (SETL) of data from two caGrid data sources, caTissue and caArray, as well as alignment and query of those sources in Corvus. We argue that semantic integration is necessary for integration of data from distributed web services and that Corvus is a useful way of accomplishing this. Our approach is generalizable and of broad utility to researchers facing similar integration challenges.
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paper_title: Semantic web for integrated network analysis in biomedicine

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The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.
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paper_title: Linked Data: Evolving the Web Into a Global Data Space

paper_content:

The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study.
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paper_title: Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL

paper_content:

Semantic Web models and technologies provide information in machine-readable languages that enable computers to access the Web more intelligently and perform tasks automatically without the direction of users. These technologies are relatively recent and advancing rapidly, creating a set of unique challenges for those developing applications. ::: ::: Semantic Web for the Working Ontologist is the essential, comprehensive resource on semantic modeling, for practitioners in health care, artificial intelligence, finance, engineering, military intelligence, enterprise architecture, and more. Focused on developing useful and reusable models, this market-leading book explains how to build semantic content (ontologies) and how to build applications that access that content. ::: ::: New in this edition: ::: ::: ::: Coverage of the latest Semantic Web tools for organizing, querying, and processing information - see details in TOC below ::: ::: Detailed information on the latest ontologies used in key web applications including ecommerce, social networking, data mining, using government data, and more ::: ::: ::: ::: ::: Updated with the latest developments and advances in Semantic Web technologies for organizing, querying, and processing information, including SPARQL, RDF and RDFS, OWL 2.0, and SKOS ::: Detailed information on the ontologies used in today's key web applications, including ecommerce, social networking, data mining, using government data, and more ::: Even more illustrative examples and case studies that demonstrate what semantic technologies are and how they work together to solve real-world problems ::: ::: Table of Contents ::: ::: 1?What Is The Semantic Web? ::: 2?Semantic Modeling ::: 3?RDF - The Basis of the Semantic Web ::: 4?SPARQL - The Query Language for RDF ::: 5?Semantic Web Application Architecture ::: 6?RDF And Inferencing ::: 7?RDF Schema Language ::: 8?RDFS-Plus ::: 9?SKOS - the Simple Knowledge Organization System ::: 10?Ontologies in the Wild: Linked Open Data and the Open Graph Project ::: 11?Basic OWL ::: 12?Counting and Sets In OWL ::: 13?MORE Ontologies in the Wild: QUDT, GoodRelations, and OBO Foundry ::: 14?Good and Bad Modeling Practices ::: 15?OWL 2.0 Levels and Logic ::: 16?Conclusions ::: 17?Frequently Asked Questions
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paper_title: Jena: a semantic Web toolkit

paper_content:

HP Labs developed the Jena toolkit to make it easier to develop applications that use the semantic Web information model and languages. Jena is a Java application programming interface that is available as an open-source download from www.hpl.hp.com/semweb/jena-top.html.
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paper_title: D2R Server – Publishing Relational Databases on the Semantic Web

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D2R Server is a tool for publishing the content of relational databases on the Semantic Web. Database content is mapped to RDF by a declarative mapping which specifies how resources are identified and how property values are generated from database content. Based on this mapping, D2R Server allows Web agents to retrieve RDF and XHTML representations of resources and to query non-RDF databases using the SPARQL query language over the SPARQL protocol. The generated representations are richly interlinked on RDF and XHTML level in order to enable browsers and crawlers to navigate database content.
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paper_title: Linked Data: Evolving the Web Into a Global Data Space

paper_content:

The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study.
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paper_title: Agents in bioinformatics , computational and systems biology

paper_content:

The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding collaborations between the agent and bioinformatics communities to develop a different (agent-based) approach of computational frameworks both for data analysis and management in bioinformatics and for systems modelling and simulation in computational and systems biology. The collaborations gave rise to applications and integrated tools that we summarize and discuss in context of the state of the art in this area. We investigate on future challenges and argue that the field should still be explored from many perspectives ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages to be used by information agents, and to the adoption of agents for computational grids.
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paper_title: RACER System Description

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RACER implements a TBox and ABox reasoner for the logic SHIQ. RACER was the first full-fledged ABox description logic system for a very expressive logic and is based on optimized sound and complete algorithms. RACER also implements a decision procedure for modal logic satisfiability problems (possibly with global axioms).
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paper_title: Semantic Wikis: A Comprehensible Introduction with Examples from the Health Sciences

paper_content:

This paper provides a concise introduction to semantic wikis. It also offers pointers to useful online resources about the subject, and presents some semantic wiki examples from the health and healthcare sciences.
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paper_title: PROVA: Rule-Based Java-Scripting for a Bioinformatics Semantic Web

paper_content:

Transparent information integration across distributed and heterogeneous data sources and computational tools is a prime concern for bioinformatics. Recently, there have been proposals for a semantic web addressing these requirements. A promising approach for such a semantic web are the integration of rules to specify and implement workflows and object-orientation to cater for computational aspects.
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paper_title: Pellet : A practical OWL-DL reasoner

paper_content:

In this paper, we present a brief overview of Pellet: a complete OWL-DL reasoner with acceptable to very good performance, extensive middleware, and a number of unique features. Pellet is the first sound and complete OWL-DL reasoner with extensive support for reasoning with individuals (including nominal support and conjunctive query), user-defined datatypes, and debugging support for ontologies. It implements several extensions to OWL-DL including a combination formalism for OWL-DL ontologies, a non-monotonic operator, and preliminary support for OWL/Rule hybrid reasoning. Pellet is written in Java and is open source.
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paper_title: Agents and the Semantic Web

paper_content:

Many challenges of bringing communicating multi-agent systems to the World Wide Web require ontologies. The integration of agent technology and ontologies could significantly affect the use of Web services and the ability to extend programs to perform tasks for users more efficiently and with less human intervention.
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paper_title: Where Are All the Intelligent Agents

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There has been much research and talk about intelligent agents, but few real-world implementations.
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paper_title: Semantic grid: scientific issues, infrastructure, and methodology

paper_content:

Creating a new interconnection environment incorporating the Internet, sensor networks, mobile devices, and the interconnection semantics.
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paper_title: Integrating biological databases

paper_content:

Recent years have seen an explosion in the amount of available biological data. More and more genomes are being sequenced and annotated, and protein and gene interaction data are accumulating. Biological databases have been invaluable for managing these data and for making them accessible. Depending on the data that they contain, the databases fulfil different functions. But, although they are architecturally similar, so far their integration has proved problematic.
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paper_title: Semantic Web Services

paper_content:

The authors propose the markup of Web services in the DAML family of Semantic Web markup languages. This markup enables a wide variety of agent technologies for automated Web service discovery, execution, composition and interoperation. The authors present one such technology for automated Web service composition.
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paper_title: Jena: a semantic Web toolkit

paper_content:

HP Labs developed the Jena toolkit to make it easier to develop applications that use the semantic Web information model and languages. Jena is a Java application programming interface that is available as an open-source download from www.hpl.hp.com/semweb/jena-top.html.
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paper_title: Web Semantics in the Clouds

paper_content:

Cloud computing refers to the use of large-scale computer clusters often built from low-cost hardware and network equipment, where resources are allocated dynamically among users of the cluster. While the paradigm is not entirely novel, recent developments in software frameworks for cloud computing are making it increasingly easy for programmers to parallelize and thereby scale-up complex data-processing tasks. This article investigates how this trend is impacting the semantic Web field and shows how cloud computing can be used to analyze, query, and reason with the massive amounts of metadata handled by semantic search engines.
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paper_title: Ontologies and the semantic web

paper_content:

How ontologies provide the semantics, as explained here with the help of Harry Potter and his owl Hedwig.
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paper_title: The Universal Protein Resource (UniProt)

paper_content:

The Universal Protein Resource (UniProt) provides the scientific community with a single, centralized, authoritative resource for protein sequences and functional information. Formed by uniting the Swiss-Prot, TrEMBL and PIR protein database activities, the UniProt consortium produces three layers of protein sequence databases: the UniProt Archive (UniParc), the UniProt Knowledgebase (UniProt) and the UniProt Reference (UniRef) databases. The UniProt Knowledgebase is a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase with extensive cross-references. This centrepiece consists of two sections: UniProt/Swiss-Prot, with fully, manually curated entries; and UniProt/TrEMBL, enriched with automated classification and annotation. During 2004, tens of thousands of Knowledgebase records got manually annotated or updated; we introduced a new comment line topic: TOXIC DOSE to store information on the acute toxicity of a toxin; the UniProt keyword list got augmented by additional keywords; we improved the documentation of the keywords and are continuously overhauling and standardizing the annotation of post-translational modifications. Furthermore, we introduced a new documentation file of the strains and their synonyms. Many new database cross-references were introduced and we started to make use of Digital Object Identifiers. We also achieved in collaboration with the Macromolecular Structure Database group at EBI an improved integration with structural databases by residue level mapping of sequences from the Protein Data Bank entries onto corresponding UniProt entries. For convenient sequence searches we provide the UniRef non-redundant sequence databases. The comprehensive UniParc database stores the complete body of publicly available protein sequence data. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). New releases are published every two weeks.
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paper_title: A journey to Semantic Web query federation in the life sciences

paper_content:

BackgroundAs interest in adopting the Semantic Web in the biomedical domain continues to grow, Semantic Web technology has been evolving and maturing. A variety of technological approaches including triplestore technologies, SPARQL endpoints, Linked Data, and Vocabulary of Interlinked Datasets have emerged in recent years. In addition to the data warehouse construction, these technological approaches can be used to support dynamic query federation. As a community effort, the BioRDF task force, within the Semantic Web for Health Care and Life Sciences Interest Group, is exploring how these emerging approaches can be utilized to execute distributed queries across different neuroscience data sources.Methods and resultsWe have created two health care and life science knowledge bases. We have explored a variety of Semantic Web approaches to describe, map, and dynamically query multiple datasets. We have demonstrated several federation approaches that integrate diverse types of information about neurons and receptors that play an important role in basic, clinical, and translational neuroscience research. Particularly, we have created a prototype receptor explorer which uses OWL mappings to provide an integrated list of receptors and executes individual queries against different SPARQL endpoints. We have also employed the AIDA Toolkit, which is directed at groups of knowledge workers who cooperatively search, annotate, interpret, and enrich large collections of heterogeneous documents from diverse locations. We have explored a tool called "FeDeRate", which enables a global SPARQL query to be decomposed into subqueries against the remote databases offering either SPARQL or SQL query interfaces. Finally, we have explored how to use the vocabulary of interlinked Datasets (voiD) to create metadata for describing datasets exposed as Linked Data URIs or SPARQL endpoints.ConclusionWe have demonstrated the use of a set of novel and state-of-the-art Semantic Web technologies in support of a neuroscience query federation scenario. We have identified both the strengths and weaknesses of these technologies. While Semantic Web offers a global data model including the use of Uniform Resource Identifiers (URI's), the proliferation of semantically-equivalent URI's hinders large scale data integration. Our work helps direct research and tool development, which will be of benefit to this community.
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paper_title: The Semantic Web in action.

paper_content:

The article describes the Semantic Web, how it functions, how it grows and what makes it different from the World Wide Web. The Semantic Web makes it possible for any computer to access information by creating a common language between any personal computers and the Internet at large. This system would enhance the World Wide Web by creating one comprehensive format that all programs would be based on. INSETS: KEY CONCEPTS;Combining Concepts;FRIEND OF A FRIEND;Which Genes Cause Heart Disease?
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paper_title: PubChem: a public information system for analyzing bioactivities of small molecules

paper_content:

PubChem (http://pubchem.ncbi.nlm.nih.gov) is a public repository for biological properties of small molecules hosted by the US National Institutes of Health (NIH). PubChem BioAssay database currently contains biological test results for more than 700 000 compounds. The goal of PubChem is to make this information easily accessible to biomedical researchers. In this work, we present a set of web servers to facilitate and optimize the utility of biological activity information within PubChem. These web-based services provide tools for rapid data retrieval, integration and comparison of biological screening results, exploratory structure–activity analysis, and target selectivity examination. This article reviews these bioactivity analysis tools and discusses their uses. Most of the tools described in this work can be directly accessed at http://pubchem.ncbi.nlm.nih.gov/assay/. URLs for accessing other tools described in this work are specified individually.
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paper_title: YeastHub : a semantic web use case for integrating data in the life sciences domain

paper_content:

Motivation: As the semantic web technology is maturing and the need for life sciences data integration over the web is growing, it is important to explore how data integration needs can be addressed by the semantic web. The main problem that we face in data integration is a lack of widely-accepted standards for expressing the syntax and semantics of the data. We address this problem by exploring the use of semantic web technologies---including resource description framework (RDF), RDF site summary (RSS), relational-database-to-RDF mapping (D2RQ) and native RDF data repository---to represent, store and query both metadata and data across life sciences datasets. ::: ::: Results: As many biological datasets are presently available in tabular format, we introduce an RDF structure into which they can be converted. Also, we develop a prototype web-based application called YeastHub that demonstrates how a life sciences data warehouse can be built using a native RDF data store (Sesame). This data warehouse allows integration of different types of yeast genome data provided by different resources in different formats including the tabular and RDF formats. Once the data are loaded into the data warehouse, RDF-based queries can be formulated to retrieve and query the data in an integrated fashion. ::: ::: Availability: The YeastHub website is accessible via the following URL: http://yeasthub.gersteinlab.org ::: ::: Contact: kei.cheung@yale.edu
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paper_title: The Protein Data Bank

paper_content:

The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
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paper_title: BioLit: integrating biological literature with databases

paper_content:

BioLit is a web server which provides metadata describing the semantic content of all open access, peer-reviewed articles which describe research from the major life sciences literature archive, PubMed Central. Specifically, these metadata include database identifiers and ontology terms found within the full text of the article. BioLit delivers these metadata in the form of XML-based article files and as a custom web-based article viewer that provides context-specific functionality to the metadata. This resource aims to integrate the traditional scientific publication directly into existing biological databases, thus obviating the need for a user to search in multiple locations for information relating to a specific item of interest, for example published experimental results associated with a particular biological database entry. As an example of a possible use of BioLit, we also present an instance of the Protein Data Bank fully integrated with BioLit data. We expect that the community of life scientists in general will be the primary end-users of the web-based viewer, while biocurators will make use of the metadata-containing XML files and the BioLit database of article data. BioLit is available at http://biolit.ucsd.edu.
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paper_title: Linked Data: Evolving the Web Into a Global Data Space

paper_content:

The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study.
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paper_title: PharmGKB: the Pharmacogenetics Knowledge Base

paper_content:

The Pharmacogenetics Knowledge Base (PharmGKB; http://www.pharmgkb.org/) contains genomic, phenotype and clinical information collected from ongoing pharmacogenetic studies. Tools to browse, query, download, submit, edit and process the information are available to registered research network members. A subset of the tools is publicly available. PharmGKB currently contains over 150 genes under study, 14 Coriell populations and a large ontology of pharmacogenetics concepts. The pharmacogenetic concepts and the experimental data are interconnected by a set of relations to form a knowledge base of information for pharmacogenetic researchers. The information in PharmGKB, and its associated tools for processing that information, are tailored for leading-edge pharmacogenetics research. The PharmGKB project was initiated in April 2000 and the first version of the knowledge base went online in February 2001.
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paper_title: Database resources of the National Center for Biotechnology Information

paper_content:

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources that operate on the data in GenBank and a variety of other biological data made available through NCBI's Web site. NCBI data retrieval resources include Entrez, PubMed, LocusLink and the Taxonomy Browser. Data analysis resources include BLAST, Electronic PCR, OrfFinder, RefSeq, UniGene, HomoloGene, Database of Single Nucleotide Polymorphisms (dbSNP), Human Genome Sequencing, Human MapViewer, GeneMap'99, Human-Mouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, Cancer Genome Anatomy Project (CGAP), SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheri-tance in Man (OMIM), the Molecular Modeling Database (MMDB) and the Conserved Domain Database (CDD). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih. gov.
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paper_title: Gene Ontology: tool for the unification of biology

paper_content:

Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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paper_title: Modeling biomedical experimental processes with OBI

paper_content:

BackgroundExperimental descriptions are typically stored as free text without using standardized terminology, creating challenges in comparison, reproduction and analysis. These difficulties impose limitations on data exchange and information retrieval.ResultsThe Ontology for Biomedical Investigations (OBI), developed as a global, cross-community effort, provides a resource that represents biomedical investigations in an explicit and integrative framework. Here we detail three real-world applications of OBI, provide detailed modeling information and explain how to use OBI.ConclusionWe demonstrate how OBI can be applied to different biomedical investigations to both facilitate interpretation of the experimental process and increase the computational processing and integration within the Semantic Web. The logical definitions of the entities involved allow computers to unambiguously understand and integrate different biological experimental processes and their relevant components.AvailabilityOBI is available at http://purl.obolibrary.org/obo/obi/2009-11-02/obi.owl
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paper_title: Relations as patterns: bridging the gap between OBO and OWL

paper_content:

BackgroundMost biomedical ontologies are represented in the OBO Flatfile Format, which is an easy-to-use graph-based ontology language. The semantics of the OBO Flatfile Format 1.2 enforces a strict predetermined interpretation of relationship statements between classes. It does not allow flexible specifications that provide better approximations of the intuitive understanding of the considered relations. If relations cannot be accurately expressed then ontologies built upon them may contain false assertions and hence lead to false inferences. Ontologies in the OBO Foundry must formalize the semantics of relations according to the OBO Relationship Ontology (RO). Therefore, being able to accurately express the intended meaning of relations is of crucial importance. Since the Web Ontology Language (OWL) is an expressive language with a formal semantics, it is suitable to de ne the meaning of relations accurately.ResultsWe developed a method to provide definition patterns for relations between classes using OWL and describe a novel implementation of the RO based on this method. We implemented our extension in software that converts ontologies in the OBO Flatfile Format to OWL, and also provide a prototype to extract relational patterns from OWL ontologies using automated reasoning. The conversion software is freely available at http://bioonto.de/obo2owl, and can be accessed via a web interface.ConclusionsExplicitly defining relations permits their use in reasoning software and leads to a more flexible and powerful way of representing biomedical ontologies. Using the extended langua0067e and semantics avoids several mistakes commonly made in formalizing biomedical ontologies, and can be used to automatically detect inconsistencies. The use of our method enables the use of graph-based ontologies in OWL, and makes complex OWL ontologies accessible in a graph-based form. Thereby, our method provides the means to gradually move the representation of biomedical ontologies into formal knowledge representation languages that incorporates an explicit semantics. Our method facilitates the use of OWL-based software in the back-end while ontology curators may continue to develop ontologies with an OBO-style front-end.
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paper_title: Bio-ontologies: current trends and future directions

paper_content:

In recent years, as a knowledge-based discipline, bioinformatics has been made more computationally amenable. After its beginnings as a technology advocated by computer scientists to overcome problems of heterogeneity, ontology has been taken up by biologists themselves as a means to consistently annotate features from genotype to phenotype. In medical informatics, artifacts called ontologies have been used for a longer period of time to produce controlled lexicons for coding schemes. In this article, we review the current position in ontologies and how they have become institutionalized within biomedicine. As the field has matured, the much older philosophical aspects of ontology have come into play. With this and the institutionalization of ontology has come greater formality. We review this trend and what benefits it might bring to ontologies and their use within biomedicine.
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paper_title: The GALEN Project

paper_content:

Abstract The GALEN project is developing language independent concept representation systems as the foundations for the next generation of multilingual coding systems. It aims to support the flexibility required to cope with the diversity amongst medical applications, while ensuring the coherence necessary for integration and re-use of terminologies. GALEN is developing a fully compositional and generative formal system for modelling concepts: the GALEN Representation and Integration Language (GRAIL) Kernel. Its goal is to overcome many of the problems with traditional coding and classification systems, in particular the combinatorial explosion of terms in enumerative systems and the generation of nonsensical terms in partially compositional systems. It will also provide a clean separation between the concept model and linguistic mechanisms which interpret that model (i.e. the words in a specific language, syntax, alternative phrasings, etc.) in order to allow the development of multilingual systems. GRAIL aims to be formally sound and produce models that are verifiable and contain no contradictions or ambiguities, with realistic human effort. A Coding Reference (CORE) Model of medical terminology covering is being developed which aims to represent the core concepts in for example pathology, anatomy and therapeutics, that have widespread applicability in medical applications. It should also provide the basis for specialist extensions according to the formal principles of GRAIL. The main results of GALEN will be delivered as a Terminology Server (TeS) which encapsulates and coordinates the functionality of the concept module, Multilingual module, and code conversion module, and also provides a uniform applications programming interface and network services for use by external applications.
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paper_title: An ontology for cell types

paper_content:

We describe an ontology for cell types that covers the prokaryotic, fungal, animal and plant worlds. It includes over 680 cell types. These cell types are classified under several generic categories and are organized as a directed acyclic graph. The ontology is available in the formats adopted by the Open Biological Ontologies umbrella and is designed to be used in the context of model organism genome and other biological databases. The ontology is freely available at http://obo.sourceforge.net/ and can be viewed using standard ontology visualization tools such as OBO-Edit and COBrA.
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paper_title: Biomedical ontologies: a functional perspective

paper_content:

The information explosion in biology makes it difficult for researchers to stay abreast of current biomedical knowledge and to make sense of the massive amounts of online information. Ontologies--specifications of the entities, their attributes and relationships among the entities in a domain of discourse--are increasingly enabling biomedical researchers to accomplish these tasks. In fact, bio-ontologies are beginning to proliferate in step with accruing biological data. The myriad of ontologies being created enables researchers not only to solve some of the problems in handling the data explosion but also introduces new challenges. One of the key difficulties in realizing the full potential of ontologies in biomedical research is the isolation of various communities involved: some workers spend their career developing ontologies and ontology-related tools, while few researchers (biologists and physicians) know how ontologies can accelerate their research. The objective of this review is to give an overview of biomedical ontology in practical terms by providing a functional perspective--describing how bio-ontologies can and are being used. As biomedical scientists begin to recognize the many different ways ontologies enable biomedical research, they will drive the emergence of new computer applications that will help them exploit the wealth of research data now at their fingertips.
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paper_title: Biodynamic Ontology: Applying BFO in the Biomedical Domain

paper_content:

We propose a modular formal ontology of the biomedical domain with two components, one for biological objects, corresponding broadly to anatomy, and one for biological processes, corresponding broadly to physiology. The result constitutes what might be described as a joint venture between two perspectives - of so-called three-dimensionalism and four-dimensionalism - which are normally regarded as incompatible. We outline an approach which allows them to be combined together, and provide examples of its application in biomedicine.
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paper_title: The Unified Medical Language System (UMLS): Integrating Biomedical Terminology

paper_content:

The Unified Medical Language System (http://umlsks.nlm.nih.gov) is a repository of biomedical vocabularies developed by the US National Library of Medicine. The UMLS integrates over 2 million names for some 900 000 concepts from more than 60 families of biomedical vocabularies, as well as 12 million relations among these concepts. Vocabularies integrated in the UMLS Metathesaurus include the NCBI taxonomy, Gene Ontology, the Medical Subject Headings (MeSH), OMIM and the Digital Anatomist Symbolic Knowledge Base. UMLS concepts are not only inter-related, but may also be linked to external resources such as GenBank. In addition to data, the UMLS includes tools for customizing the Metathesaurus (MetamorphoSys), for generating lexical variants of concept names (lvg) and for extracting UMLS concepts from text (MetaMap). The UMLS knowledge sources are updated quarterly. All vocabularies are available at no fee for research purposes within an institution, but UMLS users are required to sign a license agreement. The UMLS knowledge sources are distributed on CD-ROM and by FTP.
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paper_title: The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration

paper_content:

The value of any kind of data is greatly enhanced when it exists in a form that allows it to be integrated with other data. One approach to integration is through the annotation of multiple bodies of data using common controlled vocabularies or 'ontologies'. Unfortunately, the very success of this approach has led to a proliferation of ontologies, which itself creates obstacles to integration. The Open Biomedical Ontologies (OBO) consortium is pursuing a strategy to overcome this problem. Existing OBO ontologies, including the Gene Ontology, are undergoing coordinated reform, and new ontologies are being created on the basis of an evolving set of shared principles governing ontology development. The result is an expanding family of ontologies designed to be interoperable and logically well formed and to incorporate accurate representations of biological reality. We describe this OBO Foundry initiative and provide guidelines for those who might wish to become involved.
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paper_title: The Sequence Ontology: a tool for the unification of genome annotations

paper_content:

The Sequence Ontology (SO) is a structured controlled vocabulary for the parts of a genomic annotation. SO provides a common set of terms and definitions that will facilitate the exchange, analysis and management of genomic data. Because SO treats part-whole relationships rigorously, data described with it can become substrates for automated reasoning, and instances of sequence features described by the SO can be subjected to a group of logical operations termed extensional mereology operators.
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paper_title: Understanding and using the medical subject headings (MeSH) vocabulary to perform literature searches.

paper_content:

The United States National Library of Medicine's (NLM) MEDLINE database is the largest and most widely used medical bibliographic database. MEDLINE is manually indexed with NLM's Medical Subject Headings (MeSH) vocabulary. Using MeSH, a searcher can potentially create powerful and unambiguous MEDLINE queries. This article reviews the structure and use of MeSH, directed toward the nonexpert, and outlines how MeSH may help resolve a number of common difficulties encountered when searching MEDLINE. The increasing importance of the MEDLINE database as an information resource and the trend toward individuals performing their own bibliographic searches makes it crucial that health care professionals become familiar with MeSH.
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paper_title: Relations in biomedical ontologies

paper_content:

To enhance the treatment of relations in biomedical ontologies we advance a methodology for providing consistent and unambiguous formal definitions of the relational expressions used in such ontologies in a way designed to assist developers and users in avoiding errors in coding and annotation. The resulting Relation Ontology can promote interoperability of ontologies and support new types of automated reasoning about the spatial and temporal dimensions of biological and medical phenomena.
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paper_title: OBO and OWL: Leveraging Semantic Web Technologies for the Life Sciences

paper_content:

OBO is an ontology language that has often been used for modeling ontologies in the life sciences. Its definition is relatively informal, so, in this paper, we provide a clear specification for OBO syntax and semantics via a mapping to OWL. This mapping also allows us to apply existing Semantic Web tools and techniques to OBO. We show that Semantic Web reasoners can be used to efficiently reason with OBO ontologies. Furthermore, we show that grounding the OBO language in formal semantics is useful for the ontology development process: using an OWL reasoner, we detected a likely modeling error in one OBO ontology.
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paper_title: Knowledge networks in the age of the Semantic Web

paper_content:

The Web has become the major medium for various communities to share their knowledge. To this end, it provides an optimal environment for knowledge networks. The web offers global connectivity that is virtually instantaneous, and whose resources and documents can easily be indexed for easy searching. In the coupled realms of biomedical research and healthcare, this has become especially important where today many thousands of communities already exist that connect across academia, hospitals and industry. These communities also rely on several forms of knowledge assets, including publications, experimental data, domain-specific vocabularies and policies. Web-based communities will be one of the earlier beneficiaries of the emerging Semantic Web. With the new standards and technologies of the Semantic Web, effective utilization of knowledge networks will expand profoundly, fostering new levels of innovation and knowledge.
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paper_title: A bioinformatics analysis of the cell line nomenclature

paper_content:

Motivation: Cell lines are used extensively in biomedical research, but the nomenclature describing cell lines has not been standardized. The problems are both linguistic and experimental. Many ambiguous cell line names appear in the published literature. Users of the same cell line may refer to it in different ways, and cell lines may mutate or become contaminated without the knowledge of the user. As a first step towards rationalizing this nomenclature, we created a cell line knowledgebase (CLKB) with a well-structured collection of names and descriptive data for cell lines cultured in vitro. The objectives of this work are: (i) to assist users in extracting useful information from biomedical text and (ii) to highlight the importance of standardizing cell line names in biomedical research. This CLKB contains a broad collection of cell line names compiled from ATCC, Hyper CLDB and MeSH. In addition to names, the knowledgebase specifies relationships between cell lines. We analyze the use of cell line names in biomedical text. Issues include ambiguous names, polymorphisms in the use of names and the fact that some cell line names are also common English words. Linguistic patterns associated with the occurrence of cell line names are analyzed. Applying these patterns to find additional cell line names in the literature identifies only a small number of additional names. Annotation of microarray gene expression studies is used as a test case. The CLKB facilitates data exploration and comparison of different cell lines in support of clinical and experimental research. ::: ::: Availability: The web ontology file for this cell line collection can be downloaded at http://www.stateslab.org/data/celllineOntology/cellline.zip. ::: ::: Contact: [email protected] ::: ::: Supplementary information:Supplementary data are available at Bioinformatics online.
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paper_title: Text mining and ontologies in biomedicine: making sense of raw text

paper_content:

The volume of biomedical literature is increasing at such a rate that it is becoming difficult to locate, retrieve and manage the reported information without text mining, which aims to automatically distill information, extract facts, discover implicit links and generate hypotheses relevant to user needs. Ontologies, as conceptual models, provide the necessary framework for semantic representation of textual information. The principal link between text and an ontology is terminology, which maps terms to domain-specific concepts. This paper summarises different approaches in which ontologies have been used for text-mining applications in biomedicine.
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paper_title: BioGateway: a semantic systems biology tool for the life sciences

paper_content:

BackgroundLife scientists need help in coping with the plethora of fast growing and scattered knowledge resources. Ideally, this knowledge should be integrated in a form that allows them to pose complex questions that address the properties of biological systems, independently from the origin of the knowledge. Semantic Web technologies prove to be well suited for knowledge integration, knowledge production (hypothesis formulation), knowledge querying and knowledge maintenance.ResultsWe implemented a semantically integrated resource named BioGateway, comprising the entire set of the OBO foundry candidate ontologies, the GO annotation files, the SWISS-PROT protein set, the NCBI taxonomy and several in-house ontologies. BioGateway provides a single entry point to query these resources through SPARQL. It constitutes a key component for a Semantic Systems Biology approach to generate new hypotheses concerning systems properties. In the course of developing BioGateway, we faced challenges that are common to other projects that involve large datasets in diverse representations. We present a detailed analysis of the obstacles that had to be overcome in creating BioGateway. We demonstrate the potential of a comprehensive application of Semantic Web technologies to global biomedical data.ConclusionThe time is ripe for launching a community effort aimed at a wider acceptance and application of Semantic Web technologies in the life sciences. We call for the creation of a forum that strives to implement a truly semantic life science foundation for Semantic Systems Biology.Access to the system and supplementary information (such as a listing of the data sources in RDF, and sample queries) can be found at http://www.semantic-systems-biology.org/biogateway.
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paper_title: BioLit: integrating biological literature with databases

paper_content:

BioLit is a web server which provides metadata describing the semantic content of all open access, peer-reviewed articles which describe research from the major life sciences literature archive, PubMed Central. Specifically, these metadata include database identifiers and ontology terms found within the full text of the article. BioLit delivers these metadata in the form of XML-based article files and as a custom web-based article viewer that provides context-specific functionality to the metadata. This resource aims to integrate the traditional scientific publication directly into existing biological databases, thus obviating the need for a user to search in multiple locations for information relating to a specific item of interest, for example published experimental results associated with a particular biological database entry. As an example of a possible use of BioLit, we also present an instance of the Protein Data Bank fully integrated with BioLit data. We expect that the community of life scientists in general will be the primary end-users of the web-based viewer, while biocurators will make use of the metadata-containing XML files and the BioLit database of article data. BioLit is available at http://biolit.ucsd.edu.
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paper_title: BioCatalogue: a universal catalogue of web services for the life sciences

paper_content:

The use of Web Services to enable programmatic access to on-line bioinformatics is becoming increasingly important in the Life Sciences. However, their number, distribution and the variable quality of their documentation can make their discovery and subsequent use difficult. A Web Services registry with information on available services will help to bring together service providers and their users. The BioCatalogue (http://www.biocatalogue.org/) provides a common interface for registering, browsing and annotating Web Services to the Life Science community. Services in the BioCatalogue can be described and searched in multiple ways based upon their technical types, bioinformatics categories, user tags, service providers or data inputs and outputs. They are also subject to constant monitoring, allowing the identification of service problems and changes and the filtering-out of unavailable or unreliable resources. The system is accessible via a human-readable ‘Web 2.0’-style interface and a programmatic Web Service interface. The BioCatalogue follows a community approach in which all services can be registered, browsed and incrementally documented with annotations by any member of the scientific community.
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paper_title: Moby and Moby 2: Creatures of the Deep (Web)

paper_content:

Facile and meaningful integration of data from disparate resources is the ‘holy grail’ of bioinformatics. Some resources have begun to address this problem by providing their data using Semantic Web standards, specifically the Resource Description Framework (RDF) and the Web Ontology Language (OWL). Unfortunately, adoption of Semantic Web standards has been slow overall, and even in cases where the standards are being utilized, interconnectivity between resources is rare. In response, we have seen the emergence of centralized ‘semantic warehouses’ that collect public data from third parties, integrate it, translate it into OWL/RDF and provide it to the community as a unified and queryable resource. One limitation of the warehouse approach is that queries are confined to the resources that have been selected for inclusion. A related problem, perhaps of greater concern, is that the majority of bioinformatics data exists in the ‘Deep Web’cthat is, the data does not exist until an application or analytical tool is invoked, and therefore does not have a predictable Web address. The inability to utilize Uniform Resource Identifiers (URIs) to address this data is a barrier to its accessibility via URI-centric Semantic Web technologies. Here we examine ‘The State of the Union’ for the adoption of Semantic Web standards in the health care and life sciences domain by key bioinformatics resources, explore the nature and connectivity of several community-driven semantic warehousing projects, and report on our own progress with the CardioSHARE/Moby-2 project, which aims to make the resources of the Deep Web transparently accessible through SPARQL queries.
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paper_title: Taverna: a tool for building and running workflows of services

paper_content:

Taverna is an application that eases the use and integration of the growing number of molecular biology tools and databases available on the web, especially web services. It allows bioinformaticians to construct workflows or pipelines of services to perform a range of different analyses, such as sequence analysis and genome annotation. These high-level workflows can integrate many different resources into a single analysis. Taverna is available freely under the terms of the GNU Lesser General Public License (LGPL) from http://taverna.sourceforge.net/.
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paper_title: myGrid: personalised bioinformatics on the information grid

paper_content:

Motivation: The my Grid project aims to exploit Grid technology, with an emphasis on the Information Grid, and provide middleware layers that make it appropriate for the needs of bioinformatics. my Grid is building high level services for data and application integration such as resource discovery, workflow enactment and distributed query processing. Additional services are provided to support the scientific method and best practice found at the bench but often neglected at the workstation, notably provenance management, change notification and personalisation. Results: We give an overview of these services and their metadata. In particular, semantically rich metadata expressed using ontologies necessary to discover, select and compose services into dynamic workflows. Availability: Software is available on request from the authors and information from http://www.mygrid.org.uk.
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paper_title: Team assembly mechanisms determine collaboration network structure and team performance

paper_content:

Agents in creative enterprises are embedded in networks that inspire, support, and evaluate their work. Here, we investigate how the mechanisms by which creative teams self-assemble determine the structure of these collaboration networks. We propose a model for the self-assembly of creative teams that has its basis in three parameters: team size, the fraction of newcomers in new productions, and the tendency of incumbents to repeat previous collaborations. The model suggests that the emergence of a large connected community of practitioners can be described as a phase transition. We find that team assembly mechanisms determine both the structure of the collaboration network and team performance for teams derived from both artistic and scientific fields.
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paper_title: Bridging the semantic Web and Web 2.0 with Representational State Transfer (REST)

paper_content:

Semantic Web technologies must integrate with Web 2.0 services for both to leverage each others strengths. We argue that the REST-based design methodologies [R.T. Fielding, R.N. Taylor, Principled design of the modern web architecture, ACM Trans. Internet Technol. (TOIT) 2 (2) (2002) 115-150] of the web present the ideal mechanism through which to align the publication of semantic data with the existing web architecture. We present the design and implementation of two solutions that combine REST-based design and RDF [D. Beckett (Ed.), RDF/XML Syntax Specification (Revised), W3C Recommendation, February 10, 2004] data access: one solution for integrating existing web services and one server-side solution for creating RDF REST services. Both of these solutions enable SPARQL [E. Prud'hommeaux, A. Seaborne (Eds.), SPARQL Query Language for RDF, W3C Working Draft, March 26, 2007] to be a unifying data access layer for aligning the Semantic Web and Web 2.0.
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paper_title: Adding Semantics to Web Services Standards

paper_content:

With the increasing growth in popularity of Web services, discovery of relevant Web services becomes a significant challenge. One approach is to develop semantic Web services where by the Web services are annotated based on shared ontologies, and use these annotations for semantics-based discovery of relevant Web services. We discuss one such approach that involves adding semantics to WSDL using DAML+OIL ontologies. Our approach also uses UDDI to store these semantic annotations and search for Web services based on them. We compare our approach with another initiative to add semantics to support Web service discovery, and show how our approach may fit current standards-based industry approach better.
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paper_title: Representation and Discovery of Intelligent E-Services

paper_content:

A device for generating electric signals representing the position coordinates of a stylus on a reference surface, characterized in that it comprises a signal generator (6) that is fixed with respect to the reference surface and comprising a movable part (5) which works in conjunction with at least two potentiometers generating the voltages representing the said coordinates, the stylus (7) being a stylus for pointing on the reference surface, and mechanical linkage means being provided between this stylus and the said movable part so as to obtain a scaling down effect on the movements given to the stylus when they reach the potentiometers.
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paper_title: Towards the open service web

paper_content:

SOA4All, a collaborative European research and development project, is pioneering advanced web technology that will allow billions of parties to expose and consume IT services online. Four complementary technical advances are being integrated to create a coherent and domain-independent service delivery platform. Service-oriented architectures and service-orientation principles are being used to support the development of complex services based on distributed and reusable components. Web principles and technology are used to provide an underlying infrastructure that allows the integration of services at a world wide scale. Web 2.0 is used to structure human-machine cooperation in an efficient, user-adapted and cost effective manner. And semantic technology is used to enable service discovery.
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paper_title: Towards a cyberinfrastructure for the biological sciences: progress, visions and challenges

paper_content:

Biology is an information-driven science. Large-scale data sets from genomics, physiology, population genetics and imaging are driving research at a dizzying rate. Simultaneously, interdisciplinary collaborations among experimental biologists, theorists, statisticians and computer scientists have become the key to making effective use of these data sets. However, too many biologists have trouble accessing and using these electronic data sets and tools effectively. A 'cyberinfrastructure' is a combination of databases, network protocols and computational services that brings people, information and computational tools together to perform science in this information-driven world. This article reviews the components of a biological cyberinfrastructure, discusses current and pending implementations, and notes the many challenges that lie ahead.
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paper_title: The Design and Realisation of the myExperiment Virtual Research Environment for Social Sharing of Workflows Abstract

paper_content:

In this paper we suggest that the full scientific potential of workflows will be achieved through mechanisms for sharing and collaboration, empowering scientists to spread their experimental protocols and to benefit from those of others. To facilitate this process we have designed and built the Experimentmy Virtual Research Environment for collaboration and sharing of workflows and experiments. In contrast to systems which simply make workflows available, Experimentmy provides mechanisms to support the sharing of workflows within and across multiple communities. It achieves this by adopting a social web approach which is tailored to the particular needs of the scientist. We present the motivation, design and realisation of Experimentmy.
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paper_title: Semantic Web Services

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The authors propose the markup of Web services in the DAML family of Semantic Web markup languages. This markup enables a wide variety of agent technologies for automated Web service discovery, execution, composition and interoperation. The authors present one such technology for automated Web service composition.
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paper_title: Interoperability with Moby 1.0 – It’s Better than Sharing Your Toothbrush!

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The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.
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paper_title: SOA Principles of Service Design

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Preface xxv Chapter 1: Introduction 1 Chapter 2: Case Study Background 19 Part I: Fundamentals Chapter 3: Service-Oriented Computing and SOA 25 Chapter 4: Service-Orientation 67 Chapter 5: Understanding Design Principles 103 Part II: Design Principles Chapter 6: Service Contracts (Standardization and Design) 125 Chapter 7: Service Coupling (Intra-Service and Consumer Dependencies) 163 Chapter 8: Service Abstraction (Information Hiding and Meta Abstraction Types) 211 Chapter 9: Service Reusability (Commercial and Agnostic Design) 253 Chapter 10: Service Autonomy (Processing Boundaries and Control) 293 Chapter 11: Service Statelessness (State Management Deferral and Stateless Design) 325 Chapter 12: Service Discoverability (Interpretability and Communication) 361 Chapter 13: Service Composability (Composition Member Design and Complex Compositions) 387 Part III: Supplemental Chapter 14: Service-Orientation and Object-Orientation: A Comparison of Principles and Concepts 445 Chapter 15: Supporting Practices 477 Chapter 16: Mapping Service-Orientation Principles to Strategic Goals 497 Appendices Appendix A: Case Study Conclusion 513 Appendix B: Process Descriptions 517 Appendix C: Principles and Patterns Cross-Reference 529 Additional Resources 533 About the Author 535 About the Photos 537 Index 539
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paper_title: Model storage, exchange and integration

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The field of Computational Systems Neurobiology is maturing quickly. If one wants it to fulfil its central role in the new Integrative Neurobiology, the reuse of quantitative models needs to be facilitated. The community has to develop standards and guidelines in order to maximise the diffusion of its scientific production, but also to render it more trustworthy. In the recent years, various projects tackled the problems of the syntax and semantics of quantitative models. More recently the international initiative BioModels.net launched three projects: (1) MIRIAM is a standard to curate and annotate models, in order to facilitate their reuse. (2) The Systems Biology Ontology is a set of controlled vocabularies aimed to be used in conjunction with models, in order to characterise their components. (3) BioModels Database is a resource that allows biologists to store, search and retrieve published mathematical models of biological interests. We expect that those resources, together with the use of formal languages such as SBML, will support the fruitful exchange and reuse of quantitative models.
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paper_title: Advancing translational research with the Semantic Web

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BACKGROUND ::: A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. ::: ::: ::: RESULTS ::: We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. ::: ::: ::: CONCLUSION ::: Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base, and growing pains as the technology is scaled up. Still, the potential of interoperable knowledge sources for biomedicine, at the scale of the World Wide Web, merits continued work.
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paper_title: Structuring the Life Science Resourceome for Semantic Systems Biology: Lessons from the BioGateway Project

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The application of Semantic Web technologies in the life sci- ences for data integration is still nascent. We have recently built Bio- Gateway, an RDF store that integrates all the candidate OBO Foundry ontologies with other resources such as SWISS-PROT. In the course of developing BioGateway, we faced challenges that are common to other projects that involve large datasets in diverse formats. We present a detailed analysis of the obstacles that had to be solved in creating Bio- Gateway. In doing so, we demonstrate the potential of a comprehensive application of Semantic Web technologies to global biomedical data. The time is ripe for launching a community effort aiming at a wider accep- tance and application of Semantic Web technologies in the life sciences domain. We make a public call for the creation of a forum that strives to implement a truly semantic life science foundation of a type of Systems Biology that we named Semantic Systems Biology.
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paper_title: Semantic systems biology: enabling integrative biology via semantic web technologies

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The vast amounts of knowledge in the biomedical domain have paved the way for a new paradigm in biological research called Systems Biology, essentially an approach that relies on the integration of all available knowledge of a biological system in a single model. This approach promotes a comprehensive understanding of biological systems, driven by data integration and mathematical modelling. However, the sheer volume, variation and complexity of the current biological data pose a number of hurdles in knowledge management that need to be overcome. The Semantic Web offers various solutions to these challenges. With our initiative, named Semantic Systems Biology (SSB), we augment the systems biology approach with semantic web technologies to enable smooth data integration, rigorous knowledge representation, efficient querying, and hypothesis generation. Here we present an overview of the projects associated with the SSB initiative. Access to our resources developed within the SSB frame is provided on our website: http://www.semantic-systems-biology.org.
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paper_title: BioAssay Ontology (BAO): a semantic description of bioassays and high-throughput screening results

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BackgroundHigh-throughput screening (HTS) is one of the main strategies to identify novel entry points for the development of small molecule chemical probes and drugs and is now commonly accessible to public sector research. Large amounts of data generated in HTS campaigns are submitted to public repositories such as PubChem, which is growing at an exponential rate. The diversity and quantity of available HTS assays and screening results pose enormous challenges to organizing, standardizing, integrating, and analyzing the datasets and thus to maximize the scientific and ultimately the public health impact of the huge investments made to implement public sector HTS capabilities. Novel approaches to organize, standardize and access HTS data are required to address these challenges.ResultsWe developed the first ontology to describe HTS experiments and screening results using expressive description logic. The BioAssay Ontology (BAO) serves as a foundation for the standardization of HTS assays and data and as a semantic knowledge model. In this paper we show important examples of formalizing HTS domain knowledge and we point out the advantages of this approach. The ontology is available online at the NCBO bioportal http://bioportal.bioontology.org/ontologies/44531.ConclusionsAfter a large manual curation effort, we loaded BAO-mapped data triples into a RDF database store and used a reasoner in several case studies to demonstrate the benefits of formalized domain knowledge representation in BAO. The examples illustrate semantic querying capabilities where BAO enables the retrieval of inferred search results that are relevant to a given query, but are not explicitly defined. BAO thus opens new functionality for annotating, querying, and analyzing HTS datasets and the potential for discovering new knowledge by means of inference.
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paper_title: Controlled vocabularies and semantics in systems biology

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The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments.
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paper_title: BioAssay Ontology Annotations Facilitate Cross-Analysis of Diverse High-Throughput Screening Data Sets

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High-throughput screening data repositories, such as PubChem, represent valuable resources for the development of small-molecule chemical probes and can serve as entry points for drug discovery programs. Although the loose data format offered by PubChem allows for great flexibility, important annotations, such as the assay format and technologies employed, are not explicitly indexed. The authors have previously developed a BioAssay Ontology (BAO) and curated more than 350 assays with standardized BAO terms. Here they describe the use of BAO annotations to analyze a large set of assays that employ luciferase- and β-lactamase-based technologies. They identified promiscuous chemotypes pertaining to different subcategories of assays and specific mechanisms by which these chemotypes interfere in reporter gene assays. Results show that the data in PubChem can be used to identify promiscuous compounds that interfere nonspecifically with particular technologies. Furthermore, they show that BAO is a valuable toolset for the identification of related assays and for the systematic generation of insights that are beyond the scope of individual assays or screening campaigns.
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paper_title: CellML: its future, present and past.

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Abstract Advances in biotechnology and experimental techniques have lead to the elucidation of vast amounts of biological data. Mathematical models provide a method of analysing this data; however, there are two issues that need to be addressed: (1) the need for standards for defining cell models so they can, for example, be exchanged across the World Wide Web, and also read into simulation software in a consistent format and (2) eliminating the errors which arise with the current method of model publication. CellML has evolved to meet these needs of the modelling community. CellML is a free, open-source, eXtensible markup language based standard for defining mathematical models of cellular function. In this paper we summarise the structure of CellML, its current applications (including biological pathway and electrophysiological models), and its future development—in particular, the development of toolsets and the integration of ontologies.
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paper_title: BioGateway: a semantic systems biology tool for the life sciences

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BackgroundLife scientists need help in coping with the plethora of fast growing and scattered knowledge resources. Ideally, this knowledge should be integrated in a form that allows them to pose complex questions that address the properties of biological systems, independently from the origin of the knowledge. Semantic Web technologies prove to be well suited for knowledge integration, knowledge production (hypothesis formulation), knowledge querying and knowledge maintenance.ResultsWe implemented a semantically integrated resource named BioGateway, comprising the entire set of the OBO foundry candidate ontologies, the GO annotation files, the SWISS-PROT protein set, the NCBI taxonomy and several in-house ontologies. BioGateway provides a single entry point to query these resources through SPARQL. It constitutes a key component for a Semantic Systems Biology approach to generate new hypotheses concerning systems properties. In the course of developing BioGateway, we faced challenges that are common to other projects that involve large datasets in diverse representations. We present a detailed analysis of the obstacles that had to be overcome in creating BioGateway. We demonstrate the potential of a comprehensive application of Semantic Web technologies to global biomedical data.ConclusionThe time is ripe for launching a community effort aimed at a wider acceptance and application of Semantic Web technologies in the life sciences. We call for the creation of a forum that strives to implement a truly semantic life science foundation for Semantic Systems Biology.Access to the system and supplementary information (such as a listing of the data sources in RDF, and sample queries) can be found at http://www.semantic-systems-biology.org/biogateway.
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paper_title: Biodynamic Ontology: Applying BFO in the Biomedical Domain

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We propose a modular formal ontology of the biomedical domain with two components, one for biological objects, corresponding broadly to anatomy, and one for biological processes, corresponding broadly to physiology. The result constitutes what might be described as a joint venture between two perspectives - of so-called three-dimensionalism and four-dimensionalism - which are normally regarded as incompatible. We outline an approach which allows them to be combined together, and provide examples of its application in biomedicine.
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paper_title: From XML to RDF: how semantic web technologies will change the design of 'omic' standards

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With the ongoing rapid increase in both volume and diversity of 'omic' data (genomics, transcriptomics, proteomics, and others), the development and adoption of data standards is of paramount importance to realize the promise of systems biology. A recent trend in data standard development has been to use extensible markup language (XML) as the preferred mechanism to define data representations. But as illustrated here with a few examples from proteomics data, the syntactic and document-centric XML cannot achieve the level of interoperability required by the highly dynamic and integrated bioinformatics applications. In the present article, we discuss why semantic web technologies, as recommended by the World Wide Web consortium (W3C), expand current data standard technology for biological data representation and management.
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paper_title: RDFScape: Semantic Web meets Systems Biology

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BackgroundThe recent availability of high-throughput data in molecular biology has increased the need for a formal representation of this knowledge domain. New ontologies are being developed to formalize knowledge, e.g. about the functions of proteins. As the Semantic Web is being introduced into the Life Sciences, the basis for a distributed knowledge-base that can foster biological data analysis is laid. However, there still is a dichotomy, in tools and methodologies, between the use of ontologies in biological investigation, that is, in relation to experimental observations, and their use as a knowledge-base.ResultsRDFScape is a plugin that has been developed to extend a software oriented to biological analysis with support for reasoning on ontologies in the semantic web framework. We show with this plugin how the use of ontological knowledge in biological analysis can be extended through the use of inference. In particular, we present two examples relative to ontologies representing biological pathways: we demonstrate how these can be abstracted and visualized as interaction networks, and how reasoning on causal dependencies within elements of pathways can be implemented.ConclusionsThe use of ontologies for the interpretation of high-throughput biological data can be improved through the use of inference. This allows the use of ontologies not only as annotations, but as a knowledge-base from which new information relevant for specific analysis can be derived.
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paper_title: SenseLab: new developments in disseminating neuroscience information

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This article presents the latest developments in neuroscience information dissemination through the SenseLab suite of databases: NeuronDB, CellPropDB, ORDB, OdorDB, OdorMapDB, ModelDB and BrainPharm. These databases include information related to: (i) neuronal membrane properties and neuronal models, and (ii) genetics, genomics, proteomics and imaging studies of the olfactory system. We describe here: the new features for each database, the evolution of SenseLab’s unifying database architecture and instances of SenseLab database interoperation with other neuroscience online resources.
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paper_title: Neuroscience: Exploring the Brain

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Acclaimed for its clear, friendly style, excellent illustrations, leading author team, and compelling theme of exploration, Neuroscience: Exploring the Brain, 4e takes a fresh, contemporary approach to the study of neuroscience, emphasizing the biological basis of behavior. The authors' passion for the dynamic field of neuroscience is evident on every page, engaging students and helping them master the material. In just a few years, the field of neuroscience has been transformed by exciting new technologies and an explosion of knowledge about the brain. The human genome has been sequenced, sophisticated new methods have been developed for genetic engineering, and new methods have been introduced to enable visualization and stimulation of specific types of nerve cells and connections in the brain. The new Fourth Edition has been fully updated to reflect these and other rapid advances in the field, while honoring its commitment to be student-friendly with striking new illustrations, additional animations, and an unparalleled array of online resources.
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paper_title: Approaches to neuroscience data integration

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As the number of neuroscience databases increases, the need for neuroscience data integration grows. This paper reviews and compares several approaches, including the Neuroscience Database Gateway (NDG), Neuroscience Information Framework (NIF) and Entrez Neuron, which enable neuroscience database annotation and integration. These approaches cover a range of activities spanning from registry, discovery and integration of a wide variety of neuroscience data sources. They also provide different user interfaces for browsing, querying and displaying query results. In Entrez Neuron, for example, four different facets or tree views (neuron, neuronal property, gene and drug) are used to hierarchically organize concepts that can be used for querying a collection of ontologies. The facets are also used to define the structure of the query results.
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paper_title: SWAN: A Distributed Knowledge Infrastructure for Alzheimer Disease Research

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SWAN - a Semantic Web Application in Neuromedicine - is a project to develop an effective, integrated scientific knowledge infrastructure for Alzheimer Disease (AD) researchers, enabled by Semantic Web technology and deployed on Alzforum (www.alzforum.org), a scientific web community for AD research. This infrastructure may later be deployed for research communities in other neuromedical disorders. SWAN incorporates the full biomedical research knowledge lifecycle in its ontological model, including support for personal data organization, hypothesis generation, experimentation, lab data organization, and digital pre-publication collaboration. Community, laboratory, and personal digital resources may all be organized and interconnected using SWAN's common semantic framework.
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paper_title: The SWAN biomedical discourse ontology

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Developing cures for highly complex diseases, such as neurodegenerative disorders, requires extensive interdisciplinary collaboration and exchange of biomedical information in context. Our ability to exchange such information across sub-specialties today is limited by the current scientific knowledge ecosystem's inability to properly contextualize and integrate data and discourse in machine-interpretable form. This inherently limits the productivity of research and the progress toward cures for devastating diseases such as Alzheimer's and Parkinson's. SWAN (Semantic Web Applications in Neuromedicine) is an interdisciplinary project to develop a practical, common, semantically structured, framework for biomedical discourse initially applied, but not limited, to significant problems in Alzheimer Disease (AD) research. The SWAN ontology has been developed in the context of building a series of applications for biomedical researchers, as well as in extensive discussions and collaborations with the larger bio-ontologies community. In this paper, we present and discuss the SWAN ontology of biomedical discourse. We ground its development theoretically, present its design approach, explain its main classes and their application, and show its relationship to other ongoing activities in biomedicine and bio-ontologies.
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paper_title: Alzforum and SWAN: the present and future of scientific web communities

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Scientists drove the early development of the World Wide Web, primarily as a means for rapid communication, document sharing and data access. They have been far slower to adopt the web as a medium for building research communities. Yet, web-based communities hold great potential for accelerating the pace of scientific research. In this article, we will describe the 10-year experience of the Alzheimer Research Forum ('Alzforum'), a unique example of a thriving scientific web community, and explain the features that contributed to its success. We will then outline the SWAN (Semantic Web Applications in Neuromedicine) project, in which Alzforum curators are collaborating with informatics researchers to develop novel approaches that will enable communities to share richly contextualized information about scientific data, claims and hypotheses.
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paper_title: Life sciences on the Semantic Web: the Neurocommons and beyond

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Translational research, the effort to couple the results of basic research to clinical applications, depends on the ability to effectively answer questions using information that spans multiple disciplines. The Semantic Web, with its emphasis on combining information using standard representation languages, access to that information via standard web protocols, and technologies to leverage computation, such as in the form of inference and distributable query, offers a social and technological basis for assembling, integrating and making available biomedical knowledge at Web scale. In this article, we discuss the use of Semantic Web technology for assembling and querying biomedical knowledge from multiple sources and disciplines. We present the Neurocommons prototype knowledge base, a demonstration intended to show the feasibility and benefits of using these technologies. The prototype knowledge base can be used to experiment with and assess the scalability of current tools and methods for creating such a resource, and to elicit issues that will need to be addressed in order to expand the scope and use of it. We demonstrate the utility of the knowledge base by reviewing a few example queries that provide answers to precise questions relevant to the understanding of disease. All components of the knowledge base are freely available at http://neurocommons.org/, enabling readers to reconstruct the knowledge base and experiment with this new technology.
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paper_title: Applying semantic Web technologies to drug safety determination

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Ensuring drug safety is of paramount importance to the life sciences industry. It's critical that drugs are able not only to achieve the desired result but also to do so without harmful side effects. By identifying problems as early as possible in the drug discovery and development process, life sciences companies can avoid drug safety sagas, such as a recent example that concerned COX-2 inhibitors. Unfortunately, drug safety problems are often revealed only during clinical trials or occasionally after marketing. These challenges are becoming more acute as medicines are targeted to defined patient populations. The life sciences industry can use semantic Web technologies to integrate data more effectively across all drug discovery and development business units, thereby providing a more supportive environment for the early detection of safety-related issues. Effective integration would enable genomic data and patient profiles to be more easily related to safety, thus providing: 1) a simpler framework for determining risk-benefit for individual patients in particular treatment regimens, 2) a better mechanism to distribute new data relating to safety throughout the organization, and 3) a better decision-making environment to determine which drugs to pursue. Furthermore, semantic Web inferencing capabilities enable an intelligent decision support system or autonomous agent to reason about combined domain-specific and industry-specific knowledge and act on the conclusions drawn from this inferencing process.
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paper_title: DrugBank: a knowledgebase for drugs, drug actions and drug targets

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DrugBank is a richly annotated resource that combines detailed drug data with comprehensive drug target and drug action information. Since its first release in 2006, DrugBank has been widely used to facilitate in silico drug target discovery, drug design, drug docking or screening, drug metabolism prediction, drug interaction prediction and general pharmaceutical education. The latest version of DrugBank (release 2.0) has been expanded significantly over the previous release. With 4900 drug entries, it now contains 60% more FDA-approved small molecule and biotech drugs including 10% more ‘experimental’ drugs. Significantly, more protein target data has also been added to the database, with the latest version of DrugBank containing three times as many non-redundant protein or drug target sequences as before (1565 versus 524). Each DrugCard entry now contains more than 100 data fields with half of the information being devoted to drug/chemical data and the other half devoted to pharmacological, pharmacogenomic and molecular biological data. A number of new data fields, including food–drug interactions, drug–drug interactions and experimental ADME data have been added in response to numerous user requests. DrugBank has also significantly improved the power and simplicity of its structure query and text query searches. DrugBank is available at http://www.drugbank.ca
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paper_title: The promise of a Virtual Lab in Drug Discovery

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To date, the life sciences ‘omics’ revolution has not lived up to the expectation of boosting the drug discovery process. The major obstacle is dealing with the volume and diversity of data generated. An enhanced-science (e-science) approach based on remote collaboration, reuse of data and methods, and supported by a virtual laboratory (VL) environment promises to get the drug discovery process afloat. The creation, use and preservation of information in formalized knowledge spaces is essential to the e-science approach. VLs include Grid computation and data communication as well as generic and domain-specific tools and methods for information management, knowledge extraction and data analysis. Problem-solving environments (PSEs) are the domain-specific experimental environments of VLs. Thus, VL–PSEs can support virtual organizations, based on the changing partnerships characteristic of successful drug discovery enterprises.
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paper_title: The pharmacogenetics and pharmacogenomics knowledge base: accentuating the knowledge

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PharmGKB is a knowledge base that captures the relationships between drugs, diseases/phenotypes and genes involved in pharmacokinetics (PK) and pharmacodynamics (PD). This information includes literature annotations, primary data sets, PK and PD pathways, and expert-generated summaries of PK/PD relationships between drugs, diseases/phenotypes and genes. PharmGKB's website is designed to effectively disseminate knowledge to meet the needs of our users. PharmGKB currently has literature annotations documenting the relationship of over 500 drugs, 450 diseases and 600 variant genes. In order to meet the needs of whole genome studies, PharmGKB has added new functionalities, including browsing the variant display by chromosome and cytogenetic locations, allowing the user to view variants not located within a gene. We have developed new infrastructure for handling whole genome data, including increased methods for quality control and tools for comparison across other data sources, such as dbSNP, JSNP and HapMap data. PharmGKB has also added functionality to accept, store, display and query high throughput SNP array data. These changes allow us to capture more structured information on phenotypes for better cataloging and comparison of data. PharmGKB is available at www.pharmgkb.org.
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paper_title: Systems biology in drug discovery

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The hope of the rapid translation of 'genes to drugs' has foundered on the reality that disease biology is complex, and that drug development must be driven by insights into biological responses. Systems biology aims to describe and to understand the operation of complex biological systems and ultimately to develop predictive models of human disease. Although meaningful molecular level models of human cell and tissue function are a distant goal, systems biology efforts are already influencing drug discovery. Large-scale gene, protein and metabolite measurements ('omics') dramatically accelerate hypothesis generation and testing in disease models. Computer simulations integrating knowledge of organ and system-level responses help prioritize targets and design clinical trials. Automation of complex primary human cell–based assay systems designed to capture emergent properties can now integrate a broad range of disease-relevant human biology into the drug discovery process, informing target and compound validation, lead optimization, and clinical indication selection. These systems biology approaches promise to improve decision making in pharmaceutical development.
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paper_title: Moving towards individualized medicine with pharmacogenomics

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Individuals respond differently to drugs and sometimes the effects are unpredictable. Differences in DNA that alter the expression or function of proteins that are targeted by drugs can contribute significantly to variation in the responses of individuals. Many of the genes examined in early studies were linked to highly penetrant, single-gene traits, but future advances hinge on the more difficult challenge of elucidating multi-gene determinants of drug response. This intersection of genomics and medicine has the potential to yield a new set of molecular diagnostic tools that can be used to individualize and optimize drug therapy.
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paper_title: Improving life sciences information retrieval using semantic web technology

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The ability to retrieve relevant information is at the heart of every aspect of research and development in the life sciences industry. Information is often distributed across multiple systems and recorded in a way that makes it difficult to piece together the complete picture. Differences in data formats, naming schemes and network protocols amongst information sources, both public and private, must be overcome, and user interfaces not only need to be able to tap into these diverse information sources but must also assist users in filtering out extraneous information and highlighting the key relationships hidden within an aggregated set of information. The Semantic Web community has made great strides in proposing solutions to these problems, and many efforts are underway to apply Semantic Web techniques to the problem of information retrieval in the life sciences space. This article gives an overview of the principles underlying a Semantic Web-enabled information retrieval system: creating a unified abstraction for knowledge using the RDF semantic network model; designing semantic lenses that extract contextually relevant subsets of information; and assembling semantic lenses into powerful information displays. Furthermore, concrete examples of how these principles can be applied to life science problems including a scenario involving a drug discovery dashboard prototype called BioDash are provided.
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paper_title: The Universal Protein Resource (UniProt)

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The Universal Protein Resource (UniProt) provides the scientific community with a single, centralized, authoritative resource for protein sequences and functional information. Formed by uniting the Swiss-Prot, TrEMBL and PIR protein database activities, the UniProt consortium produces three layers of protein sequence databases: the UniProt Archive (UniParc), the UniProt Knowledgebase (UniProt) and the UniProt Reference (UniRef) databases. The UniProt Knowledgebase is a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase with extensive cross-references. This centrepiece consists of two sections: UniProt/Swiss-Prot, with fully, manually curated entries; and UniProt/TrEMBL, enriched with automated classification and annotation. During 2004, tens of thousands of Knowledgebase records got manually annotated or updated; we introduced a new comment line topic: TOXIC DOSE to store information on the acute toxicity of a toxin; the UniProt keyword list got augmented by additional keywords; we improved the documentation of the keywords and are continuously overhauling and standardizing the annotation of post-translational modifications. Furthermore, we introduced a new documentation file of the strains and their synonyms. Many new database cross-references were introduced and we started to make use of Digital Object Identifiers. We also achieved in collaboration with the Macromolecular Structure Database group at EBI an improved integration with structural databases by residue level mapping of sequences from the Protein Data Bank entries onto corresponding UniProt entries. For convenient sequence searches we provide the UniRef non-redundant sequence databases. The comprehensive UniParc database stores the complete body of publicly available protein sequence data. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). New releases are published every two weeks.
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paper_title: Towards pharmacogenomics knowledge discovery with the semantic web

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Pharmacogenomics aims to understand pharmacological response with respect to genetic variation. Essential to the delivery of better health care is the use of pharmacogenomics knowledge to answer questions about therapeutic, pharmacological or genetic aspects. Several XML markup languages have been developed to capture pharmacogenomic and related information so as to facilitate data sharing. However, recent advances in semantic web technologies have presented exciting new opportunities for pharmacogenomics knowledge discovery by representing the information with machine understandable semantics. Progress in this area is illustrated with reference to the personalized medicine project that aims to facilitate pharmacogenomics knowledge discovery through intuitive knowledge capture and sophisticated question answering using automated reasoning over expressive ontologies.
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paper_title: Database resources of the National Center for Biotechnology Information

paper_content:

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, the Genetic Testing Registry, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Probe, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page.
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paper_title: Suggested Ontology for Pharmacogenomics (SO-Pharm): Modular Construction and Preliminary Testing

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Pharmacogenomics studies the involvement of interindividual variations of DNA sequence in different drug responses (especially adverse drug reactions) Knowledge Discovery in Databases (KDD) process is a means for discovering new pharmacogenomic knowledge in biological databases However data complexity makes it necessary to guide the KDD process by representation of domain knowledge Three domains at least are in concern: genotype, drug and phenotype The approach described here aims at reusing whenever possible existing domain knowledge in order to build a modular formal representation of domain knowledge in pharmacogenomics The resulting ontology is called SO-Pharm for Suggested Ontology for Pharmacogenomics Various situations encountered during the construction process are analyzed and discussed A preliminary validation is provided by representing with SO-Pharm concepts some well-known examples of pharmacogenomic knowledge.
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paper_title: Linking Open Drug Data

paper_content:

The development of new therapies for diseases requires the integration of large amounts of biomedical data from many different sources. The goal of the Linking Open Drug Data (LODD) project is to facilitate this integration by bringing these data sources onto the Web of Linked Data. We describe the different datasets published by this project, which are strongly interlinked with other Linked Data sources and contain 8.4 million RDF triples. A use case is provided that demonstrates the benefit of this work to patients and medical researchers.
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paper_title: Pharmacogenomics: Translating Functional Genomics into Rational Therapeutics

paper_content:

Genetic polymorphisms in drug-metabolizing enzymes, transporters, receptors, and other drug targets have been linked to interindividual differences in the efficacy and toxicity of many medications. Pharmacogenomic studies are rapidly elucidating the inherited nature of these differences in drug disposition and effects, thereby enhancing drug discovery and providing a stronger scientific basis for optimizing drug therapy on the basis of each patient's genetic constitution.
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paper_title: Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL

paper_content:

Semantic Web models and technologies provide information in machine-readable languages that enable computers to access the Web more intelligently and perform tasks automatically without the direction of users. These technologies are relatively recent and advancing rapidly, creating a set of unique challenges for those developing applications. ::: ::: Semantic Web for the Working Ontologist is the essential, comprehensive resource on semantic modeling, for practitioners in health care, artificial intelligence, finance, engineering, military intelligence, enterprise architecture, and more. Focused on developing useful and reusable models, this market-leading book explains how to build semantic content (ontologies) and how to build applications that access that content. ::: ::: New in this edition: ::: ::: ::: Coverage of the latest Semantic Web tools for organizing, querying, and processing information - see details in TOC below ::: ::: Detailed information on the latest ontologies used in key web applications including ecommerce, social networking, data mining, using government data, and more ::: ::: ::: ::: ::: Updated with the latest developments and advances in Semantic Web technologies for organizing, querying, and processing information, including SPARQL, RDF and RDFS, OWL 2.0, and SKOS ::: Detailed information on the ontologies used in today's key web applications, including ecommerce, social networking, data mining, using government data, and more ::: Even more illustrative examples and case studies that demonstrate what semantic technologies are and how they work together to solve real-world problems ::: ::: Table of Contents ::: ::: 1?What Is The Semantic Web? ::: 2?Semantic Modeling ::: 3?RDF - The Basis of the Semantic Web ::: 4?SPARQL - The Query Language for RDF ::: 5?Semantic Web Application Architecture ::: 6?RDF And Inferencing ::: 7?RDF Schema Language ::: 8?RDFS-Plus ::: 9?SKOS - the Simple Knowledge Organization System ::: 10?Ontologies in the Wild: Linked Open Data and the Open Graph Project ::: 11?Basic OWL ::: 12?Counting and Sets In OWL ::: 13?MORE Ontologies in the Wild: QUDT, GoodRelations, and OBO Foundry ::: 14?Good and Bad Modeling Practices ::: 15?OWL 2.0 Levels and Logic ::: 16?Conclusions ::: 17?Frequently Asked Questions
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paper_title: Advancing translational research with the Semantic Web

paper_content:

BACKGROUND ::: A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. ::: ::: ::: RESULTS ::: We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. ::: ::: ::: CONCLUSION ::: Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base, and growing pains as the technology is scaled up. Still, the potential of interoperable knowledge sources for biomedicine, at the scale of the World Wide Web, merits continued work.
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paper_title: Medicine. The NIH Roadmap.

paper_content:

The NIH Roadmap is a set of bold initiatives aimed at accelerating medical research. These initiatives will address challenges that no single NIH institute could tackle alone, but the agency as a whole must undertake. The Roadmap identifies the most compelling opportunities in three arenas: new pathways to discovery, research teams of the future, and reengineering the clinical research enterprise.
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paper_title: Knowledge sharing and collaboration in translational research, and the DC-THERA Directory

paper_content:

Biomedical research relies increasingly on large collections of data sets and knowledge whose generation, representation and analysis often require large collaborative and interdisciplinary efforts. This dimension of ‘big data’ research calls for the development of computational tools to manage such a vast amount of data, as well as tools that can improve communication and access to information from collaborating researchers and from the wider community. Whenever research projects have a defined temporal scope, an additional issue of data management arises, namely how the knowledge generated within the project can be made available beyond its boundaries and life-time. DC-THERA is a European ‘Network of Excellence’ (NoE) that spawned a very large collaborative and interdisciplinary research community, focusing on the development of novel immunotherapies derived from fundamental research in dendritic cell immunobiology. In this article we introduce the DC-THERA Directory, which is an information system designed to support knowledge management for this research community and beyond. We present how the use of metadata and Semantic Web technologies can effectively help to organize the knowledge generated by modern collaborative research, how these technologies can enable effective data management solutions during and beyond the project lifecycle, and how resources such as the DC-THERA Directory fit into the larger context of e-science.
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paper_title: A semantic web framework to integrate cancer omics data with biological knowledge

paper_content:

BackgroundThe RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge.ResultsFor this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent.ConclusionsWe were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily.
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paper_title: Knowledge networks in the age of the Semantic Web

paper_content:

The Web has become the major medium for various communities to share their knowledge. To this end, it provides an optimal environment for knowledge networks. The web offers global connectivity that is virtually instantaneous, and whose resources and documents can easily be indexed for easy searching. In the coupled realms of biomedical research and healthcare, this has become especially important where today many thousands of communities already exist that connect across academia, hospitals and industry. These communities also rely on several forms of knowledge assets, including publications, experimental data, domain-specific vocabularies and policies. Web-based communities will be one of the earlier beneficiaries of the emerging Semantic Web. With the new standards and technologies of the Semantic Web, effective utilization of knowledge networks will expand profoundly, fostering new levels of innovation and knowledge.
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paper_title: Knowledge Integration in Biomedicine: Technology and Community

paper_content:

A bottom assembly for a hopper vehicle is adapted to permit safe pneumatic unloading as well as gravity unloading of a hopper. The bottom assembly includes a membrane mounted to be moved over and away from a hopper bottom opening, and sealing devices for insuring a secure seal for the hopper which can be easily set. A discharge manifold is connected to the hopper at a location spaced from the hopper bottom opening, and the hopper bottom opening is contained in a plane which is tilted with respect to the horizontal.
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paper_title: Knowledge sharing and collaboration in translational research, and the DC-THERA Directory

paper_content:

Biomedical research relies increasingly on large collections of data sets and knowledge whose generation, representation and analysis often require large collaborative and interdisciplinary efforts. This dimension of ‘big data’ research calls for the development of computational tools to manage such a vast amount of data, as well as tools that can improve communication and access to information from collaborating researchers and from the wider community. Whenever research projects have a defined temporal scope, an additional issue of data management arises, namely how the knowledge generated within the project can be made available beyond its boundaries and life-time. DC-THERA is a European ‘Network of Excellence’ (NoE) that spawned a very large collaborative and interdisciplinary research community, focusing on the development of novel immunotherapies derived from fundamental research in dendritic cell immunobiology. In this article we introduce the DC-THERA Directory, which is an information system designed to support knowledge management for this research community and beyond. We present how the use of metadata and Semantic Web technologies can effectively help to organize the knowledge generated by modern collaborative research, how these technologies can enable effective data management solutions during and beyond the project lifecycle, and how resources such as the DC-THERA Directory fit into the larger context of e-science.
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paper_title: Combining the Power of Taverna and caGrid: Scientific Workflows that Enable Web-Scale Collaboration

paper_content:

Service-oriented architecture represents a promising approach to integrating data and software across different institutional and disciplinary sources, thus facilitating Web-scale collaboration while avoiding the need to convert different data and software to common formats. The US National Cancer Institute's Biomedical Information Grid program seeks to create both a service-oriented infrastructure (caGrid) and a suite of data and analytic services. Workflow tools in caGrid facilitate both the use and creation of services by accelerating service discovery, composition, and orchestration tasks. The authors present caGrid's workflow requirements and explain how they met these requirements by adopting and extending the Taverna system.
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paper_title: Creating a Virtual Personal Health Record Using Mashups

paper_content:

In the telehealth domain, caregiver networks provide support to the patient in the community, often through a personal health record (PHR). Current PHR systems typically are used where data and services are delivered through a single integrated data store that limits choice, is a fixed solution, and forces providers to conform to a specific data interface. Sqwelch is a mashup maker that enables trusted collaboration between a caregiver network's members through a virtual, distributed PHR. Sqwelch provides an intuitive means for the caregiver network to create personalized mashups, while the patient retains privacy control through trust specifications.
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paper_title: S3QL: A distributed domain specific language for controlled semantic integration of life sciences data

paper_content:

BACKGROUND ::: The value and usefulness of data increases when it is explicitly interlinked with related data. This is the core principle of Linked Data. For life sciences researchers, harnessing the power of Linked Data to improve biological discovery is still challenged by a need to keep pace with rapidly evolving domains and requirements for collaboration and control as well as with the reference semantic web ontologies and standards. Knowledge organization systems (KOSs) can provide an abstraction for publishing biological discoveries as Linked Data without complicating transactions with contextual minutia such as provenance and access control.We have previously described the Simple Sloppy Semantic Database (S3DB) as an efficient model for creating knowledge organization systems using Linked Data best practices with explicit distinction between domain and instantiation and support for a permission control mechanism that automatically migrates between the two. In this report we present a domain specific language, the S3DB query language (S3QL), to operate on its underlying core model and facilitate management of Linked Data. ::: ::: ::: RESULTS ::: Reflecting the data driven nature of our approach, S3QL has been implemented as an application programming interface for S3DB systems hosting biomedical data, and its syntax was subsequently generalized beyond the S3DB core model. This achievement is illustrated with the assembly of an S3QL query to manage entities from the Simple Knowledge Organization System. The illustrative use cases include gastrointestinal clinical trials, genomic characterization of cancer by The Cancer Genome Atlas (TCGA) and molecular epidemiology of infectious diseases. ::: ::: ::: CONCLUSIONS ::: S3QL was found to provide a convenient mechanism to represent context for interoperation between public and private datasets hosted at biomedical research institutions and linked data formalisms.
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paper_title: The Life Sciences Semantic Web is Full of Creeps

paper_content:

The Semantic Web for the Life Sciences (SWLS), when realized, will dramatically improve our ability to conduct bioinformatics analyses using the vast and growing stores of web-accessible resources. This ability will be achieved through the widespread acceptance and application of standards for naming, representing, describing and accessing biological information. The W3C-led Semantic Web initiative has established most, if not all, of the standards and technologies needed to achieve a unified, global SWLS. Unfortunately, the bioinformatics community has, thus far, appeared reluctant to fully adopt them. Rather, we are seeing what could be described as ‘semantic creep’ctimid, piecemeal and ad hoc adoption of parts of standards by groups that should be stridently taking a leadership role for the community. We suggest that, at this point, the primary hindrances to the creation of the SWLS may be social rather than technological in nature, and that, like the original Web, the establishment of the SWLS will depend primarily on the will and participation of its consumers.
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Title: Semantic Web meets Integrative Biology: a survey

Section 1: INTRODUCTION
Description 1: Introduce Integrative Biology and its need for interdisciplinary integration, discussing the emergence of the Semantic Web as a global solution for data integration.

Section 2: SW IN A NUTSHELL
Description 2: Provide an overview of Semantic Web technologies, including core languages (RDF, OWL, SPARQL) and the Linked Open Data (LOD) project.

Section 3: SW MEETS IB
Description 3: Discuss how the Semantic Web applications address disciplinary gaps (data, language, knowledge, collaboration) in Integrative Biology.

Section 4: Bridge the data gap
Description 4: Explain how Semantic Web technologies and Linked Data principles help in integrating heterogeneous data sources in biology.

Section 5: Bridge the language gap
Description 5: Cover the use of domain-specific ontologies and collaborative ontology engineering to bridge terminological gaps across disciplines.

Section 6: Bridge the knowledge gap
Description 6: Describe the integration of scattered and heterogeneous knowledge resources using Semantic Web technologies.

Section 7: Bridge the collaboration gap
Description 7: Discuss the advantages of combining Web services with the Semantic Web to facilitate interdisciplinary collaborations.

Section 8: TYPICAL CASE STUDIES
Description 8: Provide case studies demonstrating the application of the Semantic Web in systems biology, integrative neuroscience, bio-pharmaceutics, and translational research.

Section 9: PERSPECTIVES, CHALLENGES AND VISIONS
Description 9: Discuss the potential of the Semantic Web for interdisciplinary integration in biology and the challenges that must be addressed for its widespread adoption.