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.
A network medicine approach to quantify distance between hereditary disease modules on the interactome
Horacio Caniza,A. Romero,A. Paccanaro
Published 2015 in Scientific Reports
ABSTRACT
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- Publication year
2015
- Venue
Scientific Reports
- Publication date
2015-12-03
- Fields of study
Biology, Medicine, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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