Identification of biomarkers for prostate cancer prognosis using a novel two-step cluster analysis

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7036 LNBI, Issue , 2011, Pages 63-74

  Chen, Xin ^a   Xu, Shizhong ^b   Wang, Yipeng ^c   McClelland, Michael ^a,d   Jia, Zhenyu ^a   Mercola, Dan ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c AltheaDx Inc   (United States)

^d Vaccine Research Institute of San Diego   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CELL COMPOSITION; CLINICAL OUTCOME; CORRELATION ANALYSIS; DIFFERENTIAL EXPRESSIONS; EM CLUSTERING; EXPRESSION DATA; GLEASON SCORES; MARGIN STATUS; PROSTATE CANCERS; PROSTATE SPECIFIC ANTIGEN; SEMINAL VESICLE; SIGNALING PATHWAYS; SIMULATION STUDIES; TISSUE SAMPLES; WNT SIGNALING PATHWAYS;

BIOINFORMATICS; CLUSTER ANALYSIS; GENE EXPRESSION; PATTERN RECOGNITION; SIGNALING; TISSUE;

DISEASES;

EID: 80455144771     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-24855-9_6     Document Type: Conference Paper

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