Exploring Gene Regulatory Interaction Networks and predicting
  therapeutic molecules for Hypopharyngeal Cancer and EGFR-mutated lung
  adenocarcinoma
Abanti Bhattacharjya Md Manowarul Islam Md Ashraf Uddin Md. Alamin Talukder AKM Azad Sunil Aryal Bikash Kumar Paul Wahia Tasnim Muhammad Ali Abdulllah Almoyad Mohammad Ali Moni
With the advent of Information technology, the Bioinformatics research field
is becoming increasingly attractive to researchers and academicians. The recent
development of various Bioinformatics toolkits has facilitated the rapid
processing and analysis of vast quantities of biological data for human
perception. Most studies focus on locating two connected diseases and making
some observations to construct diverse gene regulatory interaction networks, a
forerunner to general drug design for curing illness. For instance,
Hypopharyngeal cancer is a disease that is associated with EGFR-mutated lung
adenocarcinoma. In this study, we select EGFR-mutated lung adenocarcinoma and
Hypopharyngeal cancer by finding the Lung metastases in hypopharyngeal cancer.
To conduct this study, we collect Mircorarray datasets from GEO (Gene
Expression Omnibus), an online database controlled by NCBI. Differentially
expressed genes, common genes, and hub genes between the selected two diseases
are detected for the succeeding move. Our research findings have suggested
common therapeutic molecules for the selected diseases based on 10 hub genes
with the highest interactions according to the degree topology method and the
maximum clique centrality (MCC). Our suggested therapeutic molecules will be
fruitful for patients with those two diseases simultaneously.