Genomic evolution of cancer models: perils and opportunities
Ben-David, U., R. Beroukhim, and T. R. Golub. 2019. “Genomic Evolution of Cancer Models: Perils and Opportunities”. Nat Rev Cancer 19: 97-109.
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A dataset of images and morphological profiles of 30 000 small-molecule treatments using the Cell Painting assay
Bray, M. A., S. M. Gustafsdottir, M. H. Rohban, S. Singh, V. Ljosa, K. L. Sokolnicki, J. A. Bittker, et al. 2017. “A Dataset of Images and Morphological Profiles of 30 000 Small-Molecule Treatments Using the Cell Painting Assay”. Gigascience 6: 1-5.
WRN helicase is a synthetic lethal target in microsatellite unstable cancers
Chan, E. M., T. Shibue, J. M. McFarland, B. Gaeta, M. Ghandi, N. Dumont, A. Gonzalez, et al. 2019. “WRN Helicase Is a Synthetic Lethal Target in Microsatellite Unstable Cancers”. Nature 568: 551-56.
CRISPR-Cas9 screen reveals a MYCN-amplified neuroblastoma dependency on EZH2
Chen, L., G. Alexe, N. V. Dharia, L. Ross, A. B. Iniguez, A. S. Conway, E. J. Wang, et al. 2018. “CRISPR-Cas9 Screen Reveals a MYCN-Amplified Neuroblastoma Dependency on EZH2”. J Clin Invest 128: 446-62.
High-throughput validation of ceRNA regulatory networks
Chiu, H. S., M. R. Martinez, M. Bansal, A. Subramanian, T. R. Golub, X. Yang, P. Sumazin, and A. Califano. 2017. “High-Throughput Validation of CeRNA Regulatory Networks”. BMC Genomics 18: 418.
A Maltose-Binding Protein Fusion Construct Yields a Robust Crystallography Platform for MCL1
Clifton, M. C., D. M. Dranow, A. Leed, B. Fulroth, J. W. Fairman, J. Abendroth, K. A. Atkins, et al. 2015. “A Maltose-Binding Protein Fusion Construct Yields a Robust Crystallography Platform for MCL1”. PLoS One 10: e0125010.
Discovering the anti-cancer potential of non-oncology drugs by systematic viability profiling
Corsello, S. M., R. T. Nagari, R. D. Spangler, J. Rossen, M. Kocak, J. G. Bryan, R. Humeidi, et al. 2020. “Discovering the Anti-Cancer Potential of Non-Oncology Drugs by Systematic Viability Profiling”. Nat Cancer 1: 235-48.
Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies
Cowley, G. S., B. A. Weir, F. Vazquez, P. Tamayo, J. A. Scott, S. Rusin, A. East-Seletsky, et al. 2014. “Parallel Genome-Scale Loss of Function Screens in 216 Cancer Cell Lines for the Identification of Context-Specific Genetic Dependencies”. Sci Data 1: 140035.
Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets
Dempster, J. M., C. Pacini, S. Pantel, F. M. Behan, T. Green, J. Krill-Burger, C. M. Beaver, et al. 2019. “Agreement Between Two Large Pan-Cancer CRISPR-Cas9 Gene Dependency Data Sets”. Nat Commun 10: 5817.
Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl
JC, Caicedo, Goodman A, Karhohs KW, Cimini BA, Ackerman J, Haghighi M, Heng C, et al. 2019. “Nucleus Segmentation across Imaging Experiments: The 2018 Data Science Bowl”. Nature Methods 16 (12): 1247-53.