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Predicted mouse interactome and network-based interpretation of differentially expressed genes
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 predic...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8989236/ https://www.ncbi.nlm.nih.gov/pubmed/35390003 http://dx.doi.org/10.1371/journal.pone.0264174 |
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author | 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 |
author_facet | 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 |
author_sort | Zhang, Hai-Bo |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8989236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-89892362022-04-08 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 PLoS One Research Article 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. Public Library of Science 2022-04-07 /pmc/articles/PMC8989236/ /pubmed/35390003 http://dx.doi.org/10.1371/journal.pone.0264174 Text en © 2022 Zhang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article 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 Predicted mouse interactome and network-based interpretation of differentially expressed genes |
title | Predicted mouse interactome and network-based interpretation of differentially expressed genes |
title_full | Predicted mouse interactome and network-based interpretation of differentially expressed genes |
title_fullStr | Predicted mouse interactome and network-based interpretation of differentially expressed genes |
title_full_unstemmed | Predicted mouse interactome and network-based interpretation of differentially expressed genes |
title_short | Predicted mouse interactome and network-based interpretation of differentially expressed genes |
title_sort | predicted mouse interactome and network-based interpretation of differentially expressed genes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8989236/ https://www.ncbi.nlm.nih.gov/pubmed/35390003 http://dx.doi.org/10.1371/journal.pone.0264174 |
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