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Predicted mouse interactome and network-based interpretation of differentially expressed genes.
Zhang, Hai-Bo; Ding, Xiao-Bao; Jin, Jie; Guo, Wen-Ping; Yang, Qiao-Lei; Chen, Peng-Cheng; Yao, Heng; Ruan, Li; Tao, Yu-Tian; Chen, Xin.
Afiliación
  • Zhang HB; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics & Information Engineering, Taizhou University, Taizhou, China.
  • Ding XB; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics & Information Engineering, Taizhou University, Taizhou, China.
  • Jin J; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics & Information Engineering, Taizhou University, Taizhou, China.
  • Guo WP; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics & Information Engineering, Taizhou University, Taizhou, China.
  • Yang QL; Institute of Pharmaceutical Biotechnology, School of Medicine, Zhejiang University, Hangzhou, China.
  • Chen PC; Institute of Pharmaceutical Biotechnology, School of Medicine, Zhejiang University, Hangzhou, China.
  • Yao H; Institute of Pharmaceutical Biotechnology, School of Medicine, Zhejiang University, Hangzhou, China.
  • Ruan L; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics & Information Engineering, Taizhou University, Taizhou, China.
  • Tao YT; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics & Information Engineering, Taizhou University, Taizhou, China.
  • Chen X; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics & Information Engineering, Taizhou University, Taizhou, China.
PLoS One ; 17(4): e0264174, 2022.
Article en En | MEDLINE | ID: mdl-35390003
ABSTRACT
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Bases de Datos Genéticas / Mamíferos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals / Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Bases de Datos Genéticas / Mamíferos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals / Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: China