Aviad Tsherniak

Active 2007–2023

66
Papers
25,416
Citations
53
h-index
66
i10-index

Citations

Citations per year for Aviad Tsherniak1995: 1 citations1999: 1 citations2001: 1 citations2006: 1 citations2009: 1 citations2010: 4 citations2011: 21 citations2012: 42 citations2013: 73 citations2014: 85 citations2015: 119 citations2016: 182 citations2017: 238 citations2018: 305 citations2019: 935 citations2020: 1,420 citations2021: 1,827 citations2022: 1,515 citations2023: 1,125 citations2024: 1,809 citations2025: 1,036 citations2026: 52 citations1996–1998: no citations, so these years are not shown2000: no citations, so this year is not shown2002–2005: no citations, so these years are not shown2007–2008: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 4,149 citing papers, 30.8% of this breakdownChina: 1,902 citing papers, 14.1% of this breakdownUnited Kingdom: 885 citing papers, 6.6% of this breakdownGermany: 761 citing papers, 5.6% of this breakdownCanada: 597 citing papers, 4.4% of this breakdownItaly: 428 citing papers, 3.2% of this breakdownJapan: 354 citing papers, 2.6% of this breakdownFrance: 344 citing papers, 2.6% of this breakdownAustralia: 323 citing papers, 2.4% of this breakdownSpain: 314 citing papers, 2.3% of this breakdownSwitzerland: 296 citing papers, 2.2% of this breakdownNetherlands: 290 citing papers, 2.1% of this breakdown
0%30.8%Other 21.1%

Fields

  • Biochemistry, Genetics and Molecular Biology60.8%
  • Medicine28.4%
  • Computer Science3.5%
  • Immunology and Microbiology2.1%
  • Nursing1.3%
  • Engineering1%
  • Other2.9%

Topics

  • Cancer Genomics and Diagnostics3.7%
  • Epigenetics and DNA Methylation3.4%
  • RNA modifications and cancer3.3%
  • Protein Degradation and Inhibitors2.9%
  • CRISPR and Genetic Engineering2.9%
  • Bioinformatics and Genomic Networks2.5%
  • Other81.3%

Coauthors

All papers

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  1. Defining a Cancer Dependency Map

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , - Cell 2017 cited by 3,576

  2. Next-generation characterization of the Cancer Cell Line Encyclopedia

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Jonathan Bistline, K. Venkatesan, Anupama Reddy, Dmitriy Sonkin, Manway Liu, Joseph Lehár, Joshua M. Korn, Dale Porter, Michael D. Jones, Javad Golji, Giordano Caponigro, Jordan E. Taylor, Caitlin M. Dunning, Amanda L. Creech, Allison Warren, James M. McFarland, Mahdi Zamanighomi, Audrey Kauffmann, Nicolas Stransky, Marcin Imieliński, Yosef E. Maruvka, Andrew D. Cherniack, Aviad Tsherniak, Francisca Vázquez, Jacob D. Jaffe, Andrew A. Lane, David M. Weinstock, Cory M. Johannessen, Michael Morrissey, Frank Stegmeier, Robert Schlegel, William C. Hahn, Gad Getz, Gordon B. Mills, Jesse S. Boehm, Todd R. Golub, Levi A. Garraway, William R. Sellers - Nature 2019 cited by 3,761

  3. Computational correction of copy number effect improves specificity of CRISPR–Cas9 essentiality screens in cancer cells

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Aviad Tsherniak - Nature Genetics 2017 cited by 2,157

  4. Mitochondrial metabolism promotes adaptation to proteotoxic stress

    Authors: , , , , , , , , , , , , , , , , , , - Nature Chemical Biology 2019 cited by 623

  5. Discovering the anticancer potential of non-oncology drugs by systematic viability profiling

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Francisca Vázquez, Aravind Subramanian, Jennifer A. Roth, Joshua A. Bittker, Jesse S. Boehm, Christopher C. Mader, Aviad Tsherniak, Todd R. Golub - Nature Cancer 2020 cited by 883

  6. MTAP deletion confers enhanced dependency on the PRMT5 arginine methyltransferase in cancer cells

    Authors: , , , , , , , , , , , , , , , , , , , , - Science 2016 cited by 671

  7. Mutational processes shape the landscape of TP53 mutations in human cancer

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , - Nature Genetics 2018 cited by 598

  8. Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects

    Authors: , , , , , , , - Genome biology 2021 cited by 411

  9. Pan-cancer single-cell RNA-seq identifies recurring programs of cellular heterogeneity

    Authors: , , , , , , , , , , , , , , , , , , , , , , - Nature Genetics 2020 cited by 465

  10. WRN helicase is a synthetic lethal target in microsatellite unstable cancers

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Yuen‐Yi Tseng, Zachary D. Nagel, Alan D. D’Andrea, David E. Root, Jesse S. Boehm, Gad Getz, Sandy Chang, Todd R. Golub, Aviad Tsherniak, Francisca Vázquez, Adam J. Bass - Nature 2019 cited by 472

  11. The landscape of cancer cell line metabolism

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , - Nature Medicine 2019 cited by 578

  12. Genetic and transcriptional evolution alters cancer cell line drug response

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , - Nature 2018 cited by 987

  13. An Embryonic Diapause-like Adaptation with Suppressed Myc Activity Enables Tumor Treatment Persistence

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Constantine S. Mitsiades - Cancer Cell 2021 cited by 262

  14. Extracting Biological Insights from the Project Achilles Genome-Scale CRISPR Screens in Cancer Cell Lines

    Authors: , , , , , , - 2019 cited by 429

  15. High-throughput identification of genotype-specific cancer vulnerabilities in mixtures of barcoded tumor cell lines

    Authors: , , , , , , , , , , , , , , , , , , , , - Nature Biotechnology 2016 cited by 382

  16. β-Catenin-Driven Cancers Require a YAP1 Transcriptional Complex for Survival and Tumorigenesis

    Authors: , , , , , , , , , , , , , , , , , , , , - Cell 2012 cited by 772

  17. Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , - Cancer Discovery 2016 cited by 632

  18. Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets

    Authors: , , , , , , , , , , , , , , , , , , , , , , , - Nature Communications 2019 cited by 282

  19. Selective gene dependencies in MYCN-amplified neuroblastoma include the core transcriptional regulatory circuitry

    Authors: , , , , , , , , , , , , , , , - Nature Genetics 2018 cited by 302

  20. A first-generation pediatric cancer dependency map

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , - Nature Genetics 2021 cited by 161

  21. Global computational alignment of tumor and cell line transcriptional profiles

    Authors: , , , , , , , , - Nature Communications 2021 cited by 148

  22. Functional Genomics Identify Distinct and Overlapping Genes Mediating Resistance to Different Classes of Heterobifunctional Degraders of Oncoproteins

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Joan Levy, Daniel Auclair, Jonathan D. Licht, Jonathan J. Keats, Lawrence Boise, Benjamin L. Ebert, James E. Bradner, Nathanael S. Gray, Constantine S. Mitsiades - Cell Reports 2021 cited by 115

  23. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2

    Authors: , , , , , , , , , , , - Nature Medicine 2015 cited by 412

  24. Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration

    Authors: , , , , , , , , , , , , , - Nature Communications 2018 cited by 434