Paper Title: A bioinformatics approach for identification of the core ontologies and signature genes of pulmonary disease and associated disease

Abstract:

Background and objective: Chronic Obstructive Pulmonary Disease (COPD), Diabetes mellitus (DM), Cirrhosis (CR), Ischemic Heart Disease (IHD), Ischemic Stroke (IS), Tuberculosis (TB), Obesity (OB) diseases are related to each other. Any patient affected by any of these diseases increases the possibility of being affected by other diseases. Background studies imply that there are large numbers of similar genetic and biological features among COPD, DM, CR, IHD, IS, TB, OB. For this reason, the common gene network models among these three diseases have been explored.
Methods: Preprocessing and filtering has been applied to find the common genes among disease. Then the common genes or significant genes have been explored. Thirteen common genes among COPD, DM, CR, IHD, IS, TB, OB have been recognized. PPI, PDI, PCI, String Analysis and Enrichment, GRN have been carried out to imply the significant proteins, seeds, chemicals etc.
Results: A drug signature suggestion for the hub proteins in the PDI and PCI network. From PPIN (Generic and Tissue-Specific), GRN, GO Enrichment, String analysis with algorithm 13 most responsible hub genes are found. K-means clustering was applied to find common clusters of those 13 genes.
Conclusion: This analysis discovers the most substantial hub proteins based on biochemical, biological, and genetic relationships between common genes.