Predicted mouse interactome and network-based interpretation of differentially expressed genes.

Autor: Hai-Bo Zhang, Xiao-Bao Ding, Jie Jin, Wen-Ping Guo, Qiao-Lei Yang, Peng-Cheng Chen, Heng Yao, Li Ruan, Yu-Tian Tao, Xin Chen
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: PLoS ONE, Vol 17, Iss 4, p e0264174 (2022)
Druh dokumentu: article
ISSN: 1932-6203
45238642
DOI: 10.1371/journal.pone.0264174
Popis: The house mouse or Mus musculus has become a premier mammalian model for genetic research due to its genetic and physiological similarities to humans. It brought mechanistic insights into numerous human diseases and has been routinely used to assess drug efficiency and toxicity, as well as to predict patient responses. To facilitate molecular mechanism studies in mouse, we present the Mouse Interactome Database (MID, Version 1), which includes 155,887 putative functional associations between mouse protein-coding genes inferred from functional association evidence integrated from 9 public databases. These putative functional associations are expected to cover 19.32% of all mouse protein interactions, and 26.02% of these function associations may represent protein interactions. On top of MID, we developed a gene set linkage analysis (GSLA) web tool to annotate potential functional impacts from observed differentially expressed genes. Two case studies show that the MID/GSLA system provided precise and informative annotations that other widely used gene set annotation tools, such as PANTHER and DAVID, did not. Both MID and GSLA are accessible through the website http://mouse.biomedtzc.cn.
Databáze: Directory of Open Access Journals
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