Analysis of gene network model of Thyroid Disorder and associated diseases: A bioinformatics approach

Informatics in Medicine Unlocked

Shahin Mahmud¹  Md Manowarul Islam²  Touhid Bhuyian³  Kawsar Ahmed⁴  Tasnimul Alam Taz⁵  Bikash Kumar Paul⁵  Md Kawsar⁵ 

[1] Department of Information and Communication Technology (ICT), Mawlana Bhashani Science and Technology University (MBSTU), Santosh, Tangail, 1902, Bangladesh;Group of Bio-photomatiχ, Mawlana Bhashani Science and Technology University (MBSTU), Santosh, Tangail, 1902, Bangladesh;Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University (MBSTU), Santosh, Tangail, 1902, Bangladesh;Department of Computer Scince and Engineering, Jagannath University, Dhaka, 1100, Bangladesh;Department of Software Engineering, Daffodil International University, Sukrabad, Dhanmondi, Dhaka, Bangladesh;

关键词: High blood pressure;    Chronic kidney disease;    Thyroid disorders;    Co-expression network;    Topological properties analysis;    Gene regulatory network;   

DOI  :  

来源: DOAJ

【 摘 要 】

Chronic Kidney Disease (CKD), High Blood Pressure (HBP), and Thyroid Disorder (TD) diseases are interrelated. When human patients are affected by one of them, then the possibility of affectness by the other two diseases is increased. Background studies indicate that there are large numbers of similar biological and genetic features among HBP, CKD, and TD. For this reason, the common gene network models among these three diseases are explored. The gene number is reduced through preprocessing and filtering. Then the common genes among the selected diseases and the most significant genes are explored. After completing this process, ten common genes among HBP, CKD, and TD are recognized. This analysis identifies the most significant hub proteins based on biological, biochemical, and genetic relationships between common genes. Following these relationships, the Protein-Protein Interactions network, Co-Expression network, Enrichment Analysis, Topological properties analysis, Gene regulatory network, and Physical Interaction network are exhibited. This analysis helps us to identify similar biological and genetic features among HBP, CKD, and TD. Interaction of proteins with drug molecules enables an efficient drug design for this research. These drugs can be considered for further verification by chemical experiments.

【 授权许可】

Unknown