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

Horacio Caniza , Alfonso E Romero , Alberto Paccanaro

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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.
Original languageEnglish
Article number17658
Pages (from-to)1-10
Number of pages10
JournalScientific Reports
Early online date3 Dec 2015
Publication statusE-pub ahead of print - 3 Dec 2015


  • Disease similarity
  • Bioinformatics
  • Computer Science
  • Hereditary disease modules
  • MeSH ontology
  • Network Medicine
  • Disease gene prediction

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