A network medicine approach to quantify distance between hereditary disease modules on the interactome

We introduce a MeSH-based method that accurately quantifies similarity between heritable diseases at molecular level. This method effectively brings together the existing information about diseases that is scattered across the vast corpus of biomedical literature. We prove that sets of MeSH terms pr...

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Bibliographic Details
Published inScientific reports Vol. 5; no. 1; p. 17658
Main Authors Caniza, Horacio, Romero, Alfonso E., Paccanaro, Alberto
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 03.12.2015
Nature Publishing Group
Subjects
631/553
639/705/1042
639/705/117
692/699
Data Mining - methods
Disease
Genes
Genetic Diseases, Inborn - genetics
Hereditary diseases
Humanities and Social Sciences
Humans
Internet
Medical Subject Headings
multidisciplinary
Science
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Summary:We introduce a MeSH-based method that accurately quantifies similarity between heritable diseases at molecular level. This method effectively brings together the existing information about diseases that is scattered across the vast corpus of biomedical literature. We prove that sets of MeSH terms provide a highly descriptive representation of heritable disease and that the structure of MeSH provides a natural way of combining individual MeSH vocabularies. We show that our measure can be used effectively in the prediction of candidate disease genes. We developed a web application to query more than 28.5 million relationships between 7,574 hereditary diseases (96% of OMIM) based on our similarity measure.
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ISSN:2045-2322
2045-2322
DOI:10.1038/srep17658