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A machine learning approach for somatic mutation discovery

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Science Translational Medicine  05 Sep 2018:
Vol. 10, Issue 457, eaar7939
DOI: 10.1126/scitranslmed.aar7939

Article Information

vol. 10 no. 457

PubMed: 
Print ISSN: 
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History: 
  • Received for publication December 18, 2017
  • Resubmitted May 26, 2018
  • Accepted for publication August 16, 2018
  • .

Author Information

  1. Derrick E. Wood1,
  2. James R. White1,
  3. Andrew Georgiadis1,
  4. Beth Van Emburgh1,
  5. Sonya Parpart-Li1,
  6. Jason Mitchell1,
  7. Valsamo Anagnostou2,
  8. Noushin Niknafs2,
  9. Rachel Karchin2,3,
  10. Eniko Papp1,
  11. Christine McCord1,
  12. Peter LoVerso1,
  13. David Riley1,
  14. Luis A. Diaz Jr.4,
  15. Siân Jones1,
  16. Mark Sausen1,
  17. Victor E. Velculescu2,* and
  18. Samuel V. Angiuoli1,*
  1. 1Personal Genome Diagnostics, Baltimore, MD 21224, USA.
  2. 2The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
  3. 3Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.
  4. 4Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  1. *Corresponding author. Email: velculescu{at}jhmi.edu (V.E.V.); angiuoli{at}personalgenome.com (S.V.A.)

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