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HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis

To facilitate biomedical studies of disease mechanisms, a high-quality interactome that connects functionally related genes is needed to help investigators formulate pathway hypotheses and to interpret the biological logic of a phenotype at the biological process level. Interactions in the updated v...

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Autores principales: Guo, Wen-Ping, Ding, Xiao-Bao, Jin, Jie, Zhang, Hai-bo, Yang, Qiao-lei, Chen, Peng-Cheng, Yao, Heng, Ruan, L i, Tao, Yu-Tian, Chen, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7937034/
https://www.ncbi.nlm.nih.gov/pubmed/33677507
http://dx.doi.org/10.1093/database/baab009
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author Guo, Wen-Ping
Ding, Xiao-Bao
Jin, Jie
Zhang, Hai-bo
Yang, Qiao-lei
Chen, Peng-Cheng
Yao, Heng
Ruan, L i
Tao, Yu-Tian
Chen, Xin
author_facet Guo, Wen-Ping
Ding, Xiao-Bao
Jin, Jie
Zhang, Hai-bo
Yang, Qiao-lei
Chen, Peng-Cheng
Yao, Heng
Ruan, L i
Tao, Yu-Tian
Chen, Xin
author_sort Guo, Wen-Ping
collection PubMed
description To facilitate biomedical studies of disease mechanisms, a high-quality interactome that connects functionally related genes is needed to help investigators formulate pathway hypotheses and to interpret the biological logic of a phenotype at the biological process level. Interactions in the updated version of the human interactome resource (HIR V2) were inferred from 36 mathematical characterizations of six types of data that suggest functional associations between genes. This update of the HIR consists of 88 069 pairs of genes (23.2% functional interactions of HIR V2 are in common with the previous version of HIR), representing functional associations that are of strengths similar to those between well-studied protein interactions. Among these functional interactions, 57% may represent protein interactions, which are expected to cover 32% of the true human protein interactome. The gene set linkage analysis (GSLA) tool is developed based on the high-quality HIR V2 to identify the potential functional impacts of the observed transcriptomic changes, helping to elucidate their biological significance and complementing the currently widely used enrichment-based gene set interpretation tools. A case study shows that the annotations reported by the HIR V2/GSLA system are more comprehensive and concise compared to those obtained by the widely used gene set annotation tools such as PANTHER and DAVID. The HIR V2 and GSLA are available at http://human.biomedtzc.cn.
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spelling pubmed-79370342021-03-10 HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis Guo, Wen-Ping Ding, Xiao-Bao Jin, Jie Zhang, Hai-bo Yang, Qiao-lei Chen, Peng-Cheng Yao, Heng Ruan, L i Tao, Yu-Tian Chen, Xin Database (Oxford) Original Article To facilitate biomedical studies of disease mechanisms, a high-quality interactome that connects functionally related genes is needed to help investigators formulate pathway hypotheses and to interpret the biological logic of a phenotype at the biological process level. Interactions in the updated version of the human interactome resource (HIR V2) were inferred from 36 mathematical characterizations of six types of data that suggest functional associations between genes. This update of the HIR consists of 88 069 pairs of genes (23.2% functional interactions of HIR V2 are in common with the previous version of HIR), representing functional associations that are of strengths similar to those between well-studied protein interactions. Among these functional interactions, 57% may represent protein interactions, which are expected to cover 32% of the true human protein interactome. The gene set linkage analysis (GSLA) tool is developed based on the high-quality HIR V2 to identify the potential functional impacts of the observed transcriptomic changes, helping to elucidate their biological significance and complementing the currently widely used enrichment-based gene set interpretation tools. A case study shows that the annotations reported by the HIR V2/GSLA system are more comprehensive and concise compared to those obtained by the widely used gene set annotation tools such as PANTHER and DAVID. The HIR V2 and GSLA are available at http://human.biomedtzc.cn. Oxford University Press 2021-03-02 /pmc/articles/PMC7937034/ /pubmed/33677507 http://dx.doi.org/10.1093/database/baab009 Text en © The Author(s) 2021. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Guo, Wen-Ping
Ding, Xiao-Bao
Jin, Jie
Zhang, Hai-bo
Yang, Qiao-lei
Chen, Peng-Cheng
Yao, Heng
Ruan, L i
Tao, Yu-Tian
Chen, Xin
HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis
title HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis
title_full HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis
title_fullStr HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis
title_full_unstemmed HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis
title_short HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis
title_sort hir v2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7937034/
https://www.ncbi.nlm.nih.gov/pubmed/33677507
http://dx.doi.org/10.1093/database/baab009
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