Research ResourceCancer
A machine learning approach for somatic mutation discovery
- Derrick E. Wood1,
- James R. White1,
- Andrew Georgiadis1,
- Beth Van Emburgh1,
- Sonya Parpart-Li1,
- Jason Mitchell1,
- Valsamo Anagnostou2,
- Noushin Niknafs2,
- Rachel Karchin2,3,
- Eniko Papp1,
- Christine McCord1,
- Peter LoVerso1,
- David Riley1,
- Luis A. Diaz Jr.4,
- Siân Jones1,
- Mark Sausen1,
- Victor E. Velculescu2,* and
- Samuel V. Angiuoli1,*
- 1Personal Genome Diagnostics, Baltimore, MD 21224, USA.
- 2The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
- 3Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.
- 4Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
- ↵*Corresponding author. Email: velculescu{at}jhmi.edu (V.E.V.); angiuoli{at}personalgenome.com (S.V.A.)
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Science Translational Medicine 05 Sep 2018:
Vol. 10, Issue 457, eaar7939
DOI: 10.1126/scitranslmed.aar7939
