Disease gene identification by using graph kernels and Markov random fields

Science China Life Sciences

Volumn 57, Issue 11, 2014, Pages 1054-1063

  Chen, BoLin ^a   Li, Min ^b   Wang, JianXin ^b   Wu, Fang Xiang ^a  

^a UNIVERSITY OF SASKATCHEWAN   (Canada)

^b CENTRAL SOUTH UNIVERSITY   (China)

Author keywords

Bayesian analysis; data integration; disease gene identification; graph kernel; Markov random field

Indexed keywords

ALGORITHM; AREA UNDER THE CURVE; BAYES THEOREM; BIOLOGY; GENETIC PREDISPOSITION; HUMAN; HUMAN GENOME; LABORATORY DIAGNOSIS; MARKOV CHAIN; PHENOTYPE; PROBABILITY; PROCEDURES; RECEIVER OPERATING CHARACTERISTIC; REPRODUCIBILITY; SOFTWARE; THEORETICAL MODEL;

ALGORITHMS; AREA UNDER CURVE; BAYES THEOREM; COMPUTATIONAL BIOLOGY; FALSE POSITIVE REACTIONS; GENETIC PREDISPOSITION TO DISEASE; GENOME, HUMAN; HUMANS; MARKOV CHAINS; MODELS, THEORETICAL; PHENOTYPE; PROBABILITY; REPRODUCIBILITY OF RESULTS; ROC CURVE; SOFTWARE;

EID: 84922094426     PISSN: 16747305     EISSN: 18691889     Source Type: Journal    
DOI: 10.1007/s11427-014-4745-8     Document Type: Article

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