Application of a new probabilistic model for mining implicit associated cancer genes from OMIM and Medline

Cancer Informatics

Volumn 2, Issue , 2006, Pages 361-371

  Zhu, Shanfeng ^a   Okuno, Yasushi ^a   Tsujimoto, Gozoh ^a   Mamitsuka, Hiroshi ^a  

^a KYOTO UNIVERSITY   (Japan)

Author keywords

Cancer gene discovery; Cancer genetics; Machine learning; Probabilistic model; Text mining

Indexed keywords

IMMUNOGLOBULIN ENHANCER BINDING PROTEIN; MATRIX METALLOPROTEINASE 17; PROTEIN BAX; PROTEIN BCL 2; PROTEIN KINASE ZAP 70; PROTEIN P53; TUMOR NECROSIS FACTOR;

ALGORITHM; ARTICLE; CANCER; CANCER GENETICS; INFORMATION PROCESSING; MATHEMATICAL COMPUTING; MEDICAL LITERATURE; MEDLINE; ONCOGENE; PROBABILITY; ACCURACY; AREA UNDER THE CURVE; BRAIN CANCER; BREAST CANCER; COLORECTAL CANCER; DATA BASE; DATA MINING; LEARNING ALGORITHM; LYMPHOMA; MIXTURE ASPECT MODEL; PANCREAS CANCER; PREDICTION; PROSTATE CANCER; RECEIVER OPERATING CHARACTERISTIC; STATISTICAL MODEL; TESTIS CANCER; TUMOR GENE; VALIDATION PROCESS;

EID: 33751513075     PISSN: 11769351     EISSN: 11769351     Source Type: Journal    
DOI: 10.1177/117693510600200025     Document Type: Article

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