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

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URI
http://hdl.handle.net/20.500.14066/2788
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Author(s)
Caniza, Horacio JoseCONACYT Authority; Romero, Alfonso; Paccanaro, AlbertoCONACYT Authority
Date of publishing
2015-12-03
Type of publication
research article
Subject(s)
MESH TERMS
BIOMEDICAL LITERATURE
BIOMEDICINA
TELEMEDICINA
 
Abstract
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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