Pathway and network approaches for identification of cancer signature markers from omics data

Journal of Cancer

Volumn 6, Issue 1, 2015, Pages 54-65

  Wang, Jinlian ^a,g   Zuo, Yiming ^a,f   Man, Yan gao ^b   Avital, Itzhak ^b   Stojadinovic, Alexander ^b,c   Liu, Meng ^d   Yang, Xiaowei ^d   Varghese, Rency S ^a   Tadesse, Mahlet G ^e   Ressom, Habtom W ^a  

^a GEORGETOWN UNIVERSITY   (United States)

^b Virginia Health System   (United States)

^c WALTER REED ARMY MEDICAL CENTER   (United States)

^d CITY UNIVERSITY OF NEW YORK   (United States)

^e GEORGETOWN UNIVERSITY   (United States)

^f Virginia Polytechnic Institute and State University   (United States)

^g MOUNT SINAI SCHOOL OF MEDICINE   (United States)

Author keywords

Biological pathways; Cancer biomarker; High throughput omics data; System biology

Indexed keywords

ANTINEOPLASTIC AGENT; BIOLOGICAL MARKER; SORAFENIB; TUMOR MARKER;

ANALYTIC METHOD; BAYES THEOREM; BIOINFORMATICS; BIOTECHNOLOGY; CANCER CHEMOTHERAPY; CANCER PROGNOSIS; CHEMOEMBOLIZATION; COMPUTATIONAL FLUID DYNAMICS; DATA MINING; DIAGNOSTIC TEST ACCURACY STUDY; ENZYME LINKED IMMUNOSORBENT ASSAY; GENOMICS; GRAPH THEORY; HUMAN; IMMUNOHISTOCHEMISTRY; LIVER CELL CARCINOMA; MACHINE LEARNING; METABOLOMICS; NEOPLASM; PROTEOMICS; RECEIVER OPERATING CHARACTERISTIC; REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION; REVIEW; SENSITIVITY AND SPECIFICITY; SIGNAL TRANSDUCTION; STATISTICAL ANALYSIS; SYSTEMS BIOLOGY; THEORY; WESTERN BLOTTING;

EID: 84920879603     PISSN: None     EISSN: 18379664     Source Type: Journal    
DOI: 10.7150/jca.10631     Document Type: Review

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