Abstract:
Bioinformatics is the application of computer science and information technology to the field of biology and medicine. It involves the analysis of large amounts of biological data, such as DNA sequences, protein structures, and gene expression patterns. Bioinformatics is used to develop new methods for understanding and analyzing biological data, as well as to develop new tools and technologies for biological research. Bioinformatics is used in a variety of fields, including genomics, proteomics, and drug discovery. In this study, focus on two severe diseases which affect millions of people globally such as stress and type 2 diabetes. Stress can have a significant impact on people with type 2 diabetes. Stress can cause blood sugar levels to rise, making it difficult to manage diabetes. The purpose of this research is to use various bioinformatics methods to discover potential therapeutic drugs and functional pathways between stress and type 2 diabetes. The microarray datasets GSE183648 and GSE20966 are used for the analysis of stress and type 2 diabetes samples respectively. After the datasets have been preprocessed and filtered through the use of the R programming language, identified the common DEGs. The depiction of common DEGs is shown by venn diagram. Next, the most active genes are identified through topological properties, and PPIs are built from the similar differential expressed genes (DEGs). These five genes NTRK2, SOCS3, NEDD9, MAP3K8, and SIRPA are the most important hub genes with in the interaction network of protein-protein. According to the common DEGs, GO terms molecular function (MF), KEGG and WikiPathways are shown in this study. Gene-miRNA interaction, TF-gene regulatory network, module analysis, GO terms (Biological Process, Cellular Component), Pathways (Reactome, BioCarta, BioPlanet) are all things that could be done with this research work in the future. In last, a therapeutic drug compounds are recommended on the basis of common DEGs.
