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Gregory V. Kryukov

Researcher at Broad Institute

Publications -  75
Citations -  33867

Gregory V. Kryukov is an academic researcher from Broad Institute. The author has contributed to research in topics: Selenocysteine & Selenoprotein. The author has an hindex of 54, co-authored 73 publications receiving 28426 citations. Previous affiliations of Gregory V. Kryukov include Harvard University & University of Nebraska–Lincoln.

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The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

TL;DR: The results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents and the generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of ‘personalized’ therapeutic regimens.
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Mutational heterogeneity in cancer and the search for new cancer-associated genes

Michael S. Lawrence, +96 more
- 11 Jul 2013 - 
TL;DR: A fundamental problem with cancer genome studies is described: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds and the list includes many implausible genes, suggesting extensive false-positive findings that overshadow true driver events.
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Characterization of Mammalian Selenoproteomes

TL;DR: This work identified selenoprotein genes in sequenced mammalian genomes by methods that rely on identification of selenocysteine insertion RNA structures, the coding potential of UGA codons, and the presence of cysteine-containing homologs.
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Next-generation characterization of the Cancer Cell Line Encyclopedia

Mahmoud Ghandi, +79 more
- 08 May 2019 - 
TL;DR: The original Cancer Cell Line Encyclopedia is expanded with deeper characterization of over 1,000 cell lines, including genomic, transcriptomic, and proteomic data, and integration with drug-sensitivity and gene-dependency data, which reveals potential targets for cancer drugs and associated biomarkers.