Predicting cancer-specific vulnerability via data-driven detection of synthetic lethality

Cell

Volumn 158, Issue 5, 2014, Pages 1199-1209

  Jerby Arnon, Livnat ^a   Pfetzer, Nadja ^b   Waldman, Yedael Y ^a   McGarry, Lynn ^b   James, Daniel ^b   Shanks, Emma ^b   Seashore Ludlow, Brinton ^c   Weinstock, Adam ^a   Geiger, Tamar ^a   Clemons, Paul A ^c   Gottlieb, Eyal ^b   Ruppin, Eytan ^a  

^a TEL AVIV UNIVERSITY   (Israel)

^b BEATSON INSTITUTE FOR CANCER RESEARCH   (United Kingdom)

^c BROAD INSTITUTE OF MIT AND HARVARD   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

VON HIPPEL LINDAU PROTEIN; SMALL INTERFERING RNA;

ARTICLE; BREAST CANCER; CANCER CELL LINE; CANCER PROGNOSIS; CANCER SUSCEPTIBILITY; DRUG EFFICACY; GENE IDENTIFICATION; HUMAN; LETHALITY; ONCOGENE; PREDICTION; PRIORITY JOURNAL; SOMATIC MUTATION; SYNTHETIC LETHALITY; TUMOR SUPPRESSOR GENE; BIOLOGY; BREAST NEOPLASMS; DATA MINING; GENETICS; METABOLISM; NEOPLASMS; PATHOLOGY; PROCEDURES; TUMOR CELL LINE; WORKFLOW;

BREAST NEOPLASMS; CELL LINE, TUMOR; COMPUTATIONAL BIOLOGY; DATA MINING; GENES, TUMOR SUPPRESSOR; HUMANS; NEOPLASMS; ONCOGENES; RNA, SMALL INTERFERING; WORKFLOW;

EID: 84907333139     PISSN: 00928674     EISSN: 10974172     Source Type: Journal    
DOI: 10.1016/j.cell.2014.07.027     Document Type: Article

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