Dataset Information

A genome-wide MeSH-based literature mining system predicts implicit gene-to-gene relationships and networks.

ABSTRACT:

Background

The large amount of literature in the post-genomics era enables the study of gene interactions and networks using all available articles published for a specific organism. MeSH is a controlled vocabulary of medical and scientific terms that is used by biomedical scientists to manually index articles in the PubMed literature database. We hypothesized that genome-wide gene-MeSH term associations from the PubMed literature database could be used to predict implicit gene-to-gene relationships and networks. While the gene-MeSH associations have been used to detect gene-gene interactions in some studies, different methods have not been well compared, and such a strategy has not been evaluated for a genome-wide literature analysis. Genome-wide literature mining of gene-to-gene interactions allows ranking of the best gene interactions and investigation of comprehensive biological networks at a genome level.

Results

The genome-wide GenoMesh literature mining algorithm was developed by sequentially generating a gene-article matrix, a normalized gene-MeSH term matrix, and a gene-gene matrix. The gene-gene matrix relies on the calculation of pairwise gene dissimilarities based on gene-MeSH relationships. An optimized dissimilarity score was identified from six well-studied functions based on a receiver operating characteristic (ROC) analysis. Based on the studies with well-studied Escherichia coli and less-studied Brucella spp., GenoMesh was found to accurately identify gene functions using weighted MeSH terms, predict gene-gene interactions not reported in the literature, and cluster all the genes studied from an organism using the MeSH-based gene-gene matrix. A web-based GenoMesh literature mining program is also available at: http://genomesh.hegroup.org. GenoMesh also predicts gene interactions and networks among genes associated with specific MeSH terms or user-selected gene lists.

Conclusions

The GenoMesh algorithm and web program provide the first genome-wide, MeSH-based literature mining system that effectively predicts implicit gene-gene interaction relationships and networks in a genome-wide scope.

SUBMITTER: Xiang Z

PROVIDER: S-EPMC3852244 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Publications

A genome-wide MeSH-based literature mining system predicts implicit gene-to-gene relationships and networks.

Xiang Zuoshuang Z Qin Tingting T Qin Zhaohui S ZS He Yongqun Y

BMC systems biology 20131016

<h4>Background</h4>The large amount of literature in the post-genomics era enables the study of gene interactions and networks using all available articles published for a specific organism. MeSH is a controlled vocabulary of medical and scientific terms that is used by biomedical scientists to manually index articles in the PubMed literature database. We hypothesized that genome-wide gene-MeSH term associations from the PubMed literature database could be used to predict implicit gene-to-gene r ...[more]

PMID: 24555475

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Dataset Information

A genome-wide MeSH-based literature mining system predicts implicit gene-to-gene relationships and networks.

Background

Results

Conclusions

Publications

A genome-wide MeSH-based literature mining system predicts implicit gene-to-gene relationships and networks.

Similar Datasets

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