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Towards building a disease-phenotype knowledge base: extracting disease-manifestation relationship from literature
Author(s) -
Rong Xu,
Li Li,
QuanQiu Wang
Publication year - 2013
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btt359
Subject(s) - disease , phenome , knowledge base , phenotype , clinical phenotype , repurposing , drug repositioning , computational biology , computer science , gene , bioinformatics , drug , biology , artificial intelligence , genetics , medicine , pathology , ecology , pharmacology
Systems approaches to studying phenotypic relationships among diseases are emerging as an active area of research for both novel disease gene discovery and drug repurposing. Currently, systematic study of disease phenotypic relationships on a phenome-wide scale is limited because large-scale machine-understandable disease-phenotype relationship knowledge bases are often unavailable. Here, we present an automatic approach to extract disease-manifestation (D-M) pairs (one specific type of disease-phenotype relationship) from the wide body of published biomedical literature.

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