Identification of drug and protein-protein interaction network among stress and depression: A bioinformatics approach

The fields of data mining, computational biology, and statistics have been combined to form the massive research area of bioinformatics. In the areas of genetics, education, and healthcare, bioinformatics integrates the tools available in different fields such as computing, inventorying, performing...

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Bibliographic Details
Main Authors: Md. Abul Basar, Md. Faruk Hosen, Bikash Kumar Paul, Md. Rakibul Hasan, S.M. Shamim, Touhid Bhuyian
Format: Article
Language:English
Published: Elsevier 2023-01-01
Series:Informatics in Medicine Unlocked
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914823000163
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Summary:The fields of data mining, computational biology, and statistics have been combined to form the massive research area of bioinformatics. In the areas of genetics, education, and healthcare, bioinformatics integrates the tools available in different fields such as computing, inventorying, performing statistical analyses, and collecting and processing genomic data. Stress and depression are two of the most severe mental disorders that affect people of all ages, including children and adults. The goal of this study was to look into the relationship between genetic alterations and the two diseases mentioned above as well as to develop a PPI network or related channel. The first step is to determine whether or not there is a biological relationship between them. This would assist us in connecting both of them as well as building therapeutic drugs that are effective against stress and depression disorders. Using R programs, the genes that are responsible for different diseases are acquired, pre-processed, analyzed, and mined in order to better understand them. During the study, a novel pathway was discovered. Based on common genes between the two diseases studied, the PPI network, gene-miRNA interaction, TF-gene interaction, and PDI network were established. This data can help us better understand how the PPI network binds to its ligands. We anticipate that our study will contribute to the development of new drugs for stress and depression.
ISSN:2352-9148