Brendan J. Frey

Active 1995–2024

191
Papers
44,427
Citations
70
h-index
142
i10-index

Citations

Citations per year for Brendan J. Frey1886: 1 citations1965: 1 citations1967: 1 citations1974: 1 citations1978: 1 citations1983: 3 citations1986: 3 citations1987: 1 citations1988: 1 citations1992: 1 citations1994: 2 citations1995: 6 citations1996: 14 citations1997: 20 citations1998: 37 citations1999: 69 citations2000: 111 citations2001: 188 citations2002: 215 citations2003: 237 citations2004: 297 citations2005: 426 citations2006: 463 citations2007: 609 citations2008: 653 citations2009: 730 citations2010: 873 citations2011: 846 citations2012: 883 citations2013: 934 citations2014: 996 citations2015: 1,067 citations2016: 1,211 citations2017: 1,446 citations2018: 1,580 citations2019: 2,183 citations2020: 2,119 citations2021: 1,911 citations2022: 1,401 citations2023: 1,117 citations2024: 1,203 citations2025: 757 citations2026: 163 citations1887–1964: no citations, so these years are not shown1966: no citations, so this year is not shown1968–1973: no citations, so these years are not shown1975–1977: no citations, so these years are not shown1979–1982: no citations, so these years are not shown1984–1985: no citations, so these years are not shown1989–1991: no citations, so these years are not shown1993: no citations, so this year is not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 7,615 citing papers, 25.5% of this breakdownChina: 5,217 citing papers, 17.5% of this breakdownUnited Kingdom: 1,897 citing papers, 6.3% of this breakdownCanada: 1,673 citing papers, 5.6% of this breakdownGermany: 1,391 citing papers, 4.6% of this breakdownFrance: 1,009 citing papers, 3.4% of this breakdownItaly: 879 citing papers, 2.9% of this breakdownAustralia: 855 citing papers, 2.9% of this breakdownJapan: 722 citing papers, 2.4% of this breakdownSwitzerland: 592 citing papers, 2% of this breakdownSpain: 587 citing papers, 2% of this breakdownIndia: 546 citing papers, 1.8% of this breakdown
0%25.5%Other 23.1%

Fields

  • Computer Science45.3%
  • Biochemistry, Genetics and Molecular Biology28.6%
  • Engineering11%
  • Medicine4.2%
  • Neuroscience3.1%
  • Physics and Astronomy2%
  • Other5.8%

Topics

  • RNA Research and Splicing4.1%
  • RNA modifications and cancer3.1%
  • RNA and protein synthesis mechanisms3.1%
  • Error Correcting Code Techniques3%
  • Advanced Wireless Communication Techniques2.4%
  • Advanced Image and Video Retrieval Techniques2.1%
  • Other82.2%

Coauthors

All papers

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  1. Clustering by Passing Messages Between Data Points

    Authors: , - Science 2007 cited by 6,907

  2. Factor graphs and the sum-product algorithm

    Authors: , , - IEEE Transactions on Information Theory, IEEE Trans. Inf. Theory 2001 cited by 6,481

  3. Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

    Authors: , , , - Nature Biotechnology 2015 cited by 3,163

  4. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing

    Authors: , , , , - Nature Genetics 2008 cited by 4,023

  5. Adversarial Autoencoders

    Authors: , , , , - arXiv (Cornell University), CoRR 2015 cited by 1,050

  6. k-Sparse Autoencoders

    Authors: , - ICLR (Poster) 2014 cited by 261

  7. A compendium of RNA-binding motifs for decoding gene regulation

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Elissa P. Lei, Andrew G. Fraser, Benjamin J. Blencowe, Quaid Morris, Timothy R. Hughes - Nature, Nat. 2013 cited by 1,646

  8. Deep learning in biomedicine

    Authors: , , , - Nature Biotechnology 2018 cited by 604

  9. The human splicing code reveals new insights into the genetic determinants of disease

    Authors: , , , , , , , , , , , , , , , , - Science 2014 cited by 1,318

  10. Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Wilson W. L. Sung, Fiona J. Tsoi, John Wei, Lizhen Xu, Anne-Marie Tasse, Emily Kirby, William Van Etten, Simon Twigger, Wendy Roberts, Irene Drmic, Sanne Jilderda, Bonnie MacKinnon Modi, Barbara Kellam, Michael J. Szego, Cheryl Cytrynbaum, Rosanna Weksberg, Lonnie Zwaigenbaum, Marc Woodbury‐Smith, Jessica Brian, Lili Senman, Alana Iaboni, Krissy A.R. Doyle‐Thomas, Ann Thompson, Christina Chrysler, Jonathan Leef, Tal Savion‐Lemieux, Isabel M. Smith, Xudong Liu, Rob Nicolson, Vicki Seifer, Angie Fedele, Edwin H. Cook, Stephen R. Dager, Annette Estes, Louise Gallagher, Beth A. Malow, Jeremy Parr, Sarah Spence, Jacob Vorstman, Brendan J. Frey, James Robinson, Lisa J. Strug, Bridget A. Fernandez, Mayada Elsabbagh, Melissa T. Carter, Joachim Hallmayer, Bartha Maria Knoppers, Evdokia Anagnostou, Péter Szatmári, Robert H. Ring, David Glazer, Mathew T. Pletcher, Stephen W. Scherer - Nature Neuroscience 2017 cited by 936

  11. Widespread intron retention in mammals functionally tunes transcriptomes

    Authors: , , , , , , , , - Genome Research 2014 cited by 702

  12. The Evolutionary Landscape of Alternative Splicing in Vertebrate Species

    Authors: , , , , , , , , , , , , , , , , - Science 2012 cited by 1,156

  13. The "Wake-Sleep" Algorithm for Unsupervised Neural Networks

    Authors: , , , - Science 1995 cited by 1,125

  14. Deciphering the splicing code

    Authors: , , , , , , , - Nature, Nat. 2010 cited by 936

  15. Classifying and segmenting microscopy images with deep multiple instance learning

    Authors: , , - Bioinformatics, Bioinform. 2016 cited by 449

  16. C2H2 zinc finger proteins greatly expand the human regulatory lexicon

    Authors: , , , , , , , , , , , , - Nature Biotechnology 2015 cited by 376

  17. Deep learning of the tissue-regulated splicing code

    Authors: , , , - Bioinformatics, Bioinform. 2014 cited by 487

  18. Machine Learning in Genomic Medicine: A Review of Computational Problems and Data Sets

    Authors: , , , - IEEE, Proc. IEEE 2015 cited by 285

  19. Generating and designing DNA with deep generative models

    Authors: , , , , - arXiv (Cornell University), CoRR 2017 cited by 110

  20. Whole-genome sequencing expands diagnostic utility and improves clinical management in paediatric medicine

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Mayada Helal, Stacy Hewson, Michal Inbar‐Feigenberg, Pekka Kannus, Natalya Karp, Raymond H. Kim, Jonathan B. Kronick, Eriskay Liston, H. Robson MacDonald, Saadet Mercimek‐Mahmutoglu, Roberto Mendoza‐Londono, Enas Nasr, Graeme Nimmo, Nicole Parkinson, Nada Quercia, Julian Raiman, Maian Roifman, Andreas Schulze, Andrea Shugar, Cheryl Shuman, Pierre Sinajon, Komudi Siriwardena, Rosanna Weksberg, Grace Yoon, Chris Carew, Raith Erickson, Richard A. Leach, Robert J. Klein, Peter N. Ray, M. Stephen Meyn, Stephen W. Scherer, Ronald D. Cohn, Christian R. Marshall - npj Genomic Medicine 2016 cited by 377

  21. MBNL proteins repress ES-cell-specific alternative splicing and reprogramming

    Authors: , , , , , , , , , , , , , , , , , , , , , , - Nature 2013 cited by 350

  22. Non-metric affinity propagation for unsupervised image categorization

    Authors: , - IEEE 11th International Conference on Computer Vision, ICCV 2007 cited by 302

  23. A graph neural network approach for molecule carcinogenicity prediction

    Authors: , , , , , - Bioinformatics, Bioinform. 2022 cited by 34

  24. Automated analysis of high‐content microscopy data with deep learning

    Authors: , , , , , , - Molecular Systems Biology 2017 cited by 298