A brief overview on the BioPAX and SBML standards for formal presentation of complex biological knowledge
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paper_title: A vision for the future of genomics research

paper_content:

The completion of a high-quality, comprehensive sequence of the human genome, in this fiftieth anniversary year of the discovery of the double-helical structure of DNA, is a landmark event. The genomic era is now a reality. In contemplating a vision for the future of genomics research,it is appropriate to consider the remarkable path that has brought us here. The rollfold (Figure 1) shows a timeline of landmark accomplishments in genetics and genomics, beginning with Gregor Mendel’s discovery of the laws of heredity and their rediscovery in the early days of the twentieth century.Recognition of DNA as the hereditary material, determination of its structure, elucidation of the genetic code, development of recombinant DNA technologies, and establishment of increasingly automatable methods for DNA sequencing set the stage for the Human Genome Project (HGP) to begin in 1990 (see also www.nature.com/nature/DNA50). Thanks to the vision of the original planners, and the creativity and determination of a legion of talented scientists who decided to make this project their overarching focus, all of the initial objectives of the HGP have now been achieved at least two years ahead of expectation, and a revolution in biological research has begun. The project’s new research strategies and experimental technologies have generated a steady stream of ever-larger and more complex genomic data sets that have poured into public databases and have transformed the study of virtually all life processes. The genomic approach of technology development and large-scale generation of community resource data sets has introduced an important new dimension into biological and biomedical research. Interwoven advances in genetics, comparative genomics, highthroughput biochemistry and bioinformatics
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paper_title: Mathematics Is Biology's Next Microscope, Only Better; Biology Is Mathematics' Next Physics, Only Better

paper_content:

Although mathematics has long been intertwined with the biological sciences, an explosive synergy between biology and mathematics seems poised to enrich and extend both fields greatly in the coming decades (Levin 1992; Murray 1993; Jungck 1997; Hastings et al. 2003; Palmer et al. 2003; Hastings and Palmer 2003). Biology will increasingly stimulate the creation of qualitatively new realms of mathematics. Why? In biology, ensemble properties emerge at each level of organization from the interactions of heterogeneous biological units at that level and at lower and higher levels of organization (larger and smaller physical scales, faster and slower temporal scales). New mathematics will be required to cope with these ensemble properties and with the heterogeneity of the biological units that compose ensembles at each level.
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paper_title: A minimal cascade model for the mitotic oscillator involving cyclin and cdc2 kinase

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Abstract ::: A minimal model for the mitotic oscillator is presented. The model, built on recent experimental advances, is based on the cascade of post-translational modification that modulates the activity of cdc2 kinase during the cell cycle. The model pertains to the situation encountered in early amphibian embryos, where the accumulation of cyclin suffices to trigger the onset of mitosis. In the first cycle of the bicyclic cascade model, cyclin promotes the activation of cdc2 kinase through reversible dephosphorylation, and in the second cycle, cdc2 kinase activates a cyclin protease by reversible phosphorylation. That cyclin activates cdc2 kinase while the kinase triggers the degradation of cyclin has suggested that oscillations may originate from such a negative feedback loop [Felix, M. A., Labbe, J. C., Doree, M., Hunt, T. & Karsenti, E. (1990) Nature (London) 346, 379-382]. This conjecture is corroborated by the model, which indicates that sustained oscillations of the limit cycle type can arise in the cascade, provided that a threshold exists in the activation of cdc2 kinase by cyclin and in the activation of cyclin proteolysis by cdc2 kinase. The analysis shows how miototic oscillations may readily arise from time lags associated with these thresholds and from the delayed negative feedback provided by cdc2-induced cyclin degradation. A mechanism for the origin of the thresholds is proposed in terms of the phenomenon of zero-order ultrasensitivity previously described for biochemical systems regulated by covalent modification.
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paper_title: CellML: its future, present and past.

paper_content:

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: The HUPO PSI's Molecular Interaction format—a community standard for the representation of protein interaction data

paper_content:

A major goal of proteomics is the complete description of the protein interaction network underlying cell physiology. A large number of small scale and, more recently, large-scale experiments have contributed to expanding our understanding of the nature of the interaction network. However, the necessary data integration across experiments is currently hampered by the fragmentation of publicly available protein interaction data, which exists in different formats in databases, on authors' websites or sometimes only in print publications. Here, we propose a community standard data model for the representation and exchange of protein interaction data. This data model has been jointly developed by members of the Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organization (HUPO), and is supported by major protein interaction data providers, in particular the Biomolecular Interaction Network Database (BIND), Cellzome (Heidelberg, Germany), the Database of Interacting Proteins (DIP), Dana Farber Cancer Institute (Boston, MA, USA), the Human Protein Reference Database (HPRD), Hybrigenics (Paris, France), the European Bioinformatics Institute's (EMBL-EBI, Hinxton, UK) IntAct, the Molecular Interactions (MINT, Rome, Italy) database, the Protein-Protein Interaction Database (PPID, Edinburgh, UK) and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, EMBL, Heidelberg, Germany).
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Title: A brief overview on the BioPAX and SBML standards for formal presentation of complex biological knowledge

Section 1: Background
Description 1: This section provides an introduction to the need for standards in representing biological network data, challenges faced, and the emergence of BioPAX and SBML as solutions.

Section 2: Biological network models
Description 2: This section describes what biological network models are and their significance in understanding complex molecular systems.

Section 3: A simple example of a biological network model
Description 3: This section offers a specific example of a biological network model, demonstrating how nodes and edges represent biomolecules and their interactions.

Section 4: Standards for biological network information
Description 4: This section discusses the various standards available for representing biological network information, focusing specifically on BioPAX and SBML.

Section 5: Biological Pathways Exchange Language (BioPAX 2)
Description 5: This section details the BioPAX standard, its current version, scope, and functionality.

Section 6: A brief characterization of the BioPAX network model
Description 6: This section explores the structure and characteristics of a BioPAX model, including its hierarchical class structure and types of interactions and entities it represents.

Section 7: Rredland tool for R/BioConductor
Description 7: This section overviews the Rredland package within the R/BioConductor project for BioPAX data analysis, its current capabilities, and limitations.

Section 8: Systems Biology Markup Language (SBML 2)
Description 8: This section introduces SBML, its target applications, supported databases, and computational tools.

Section 9: A brief characterization of the SBML model
Description 9: This section provides details on the SBML model's structure, including the species, compartments, reactions, and the mathematical descriptions used.

Section 10: Discussion
Description 10: This section compares and contrasts BioPAX and SBML, outlining their compatibility, detailed representations, and potential future developments and extensions.