Inferring disease association using clinical factors in a combinatorial manner and their use in drug repositioning | Zendy

JinMyung Jung | Zendy; Doheon Lee | Zendy

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Inferring disease association using clinical factors in a combinatorial manner and their use in drug repositioning

Author(s) -

JinMyung Jung,

Doheon Lee

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/btt327

Subject(s) - disease , association (psychology) , identification (biology) , association rule learning , national health and nutrition examination survey , machine learning , computer science , medicine , data mining , biology , psychology , pathology , environmental health , population , botany , psychotherapist

Complex physiological relationships exist among human diseases. Thus, the identification of disease associations could provide new methods of disease care and diagnosis. To this end, numerous studies have investigated disease associations. However, combinatorial effect of physiological factors, which is the main characteristic of biological systems, has not been considered in most previous studies.

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