dc.creatorCaniza, Horacio Jose
dc.creatorRomero, Alfonso
dc.creatorPaccanaro, Alberto
dc.date2022-04-05T00:22:49Z
dc.date2022-04-05T00:22:49Z
dc.date2015-12-03
dc.date.accessioned2023-09-25T13:30:35Z
dc.date.available2023-09-25T13:30:35Z
dc.identifierhttp://hdl.handle.net/20.500.14066/2788
dc.identifier10.1038/srep17658
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8806848
dc.descriptionWe 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.
dc.descriptionCONACYT – Consejo Nacional de Ciencia y Tecnología
dc.descriptionPROCIENCIA
dc.languageeng
dc.relation14-INV-088
dc.rightsopen access
dc.subject1303 I+D en relación con las Ciencias médicas
dc.subjectMESH TERMS
dc.subjectBIOMEDICAL LITERATURE
dc.subjectBIOMEDICINA
dc.subjectTELEMEDICINA
dc.subjectTERMINOLOGIA
dc.titleA network medicine approach to quantify distance between hereditary disease modules on the interactome
dc.typeresearch article


Este ítem pertenece a la siguiente institución