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A deep learning system can accurately classify primary and metastatic cancers based on patterns of passenger mutations
Wei Jiao, Gurnit Atwal, Paz Polak, Rosa Karlic, Edwin Cuppen, Alexandra Danyi, Jeroen de Ridder, Carla van Herpen, Martijn P Lolkema, Neeltje Steeghs, Gad Getz, Quaid D Morris, Lincoln D. Stein, PCAWG Pathology & Clinical Correlates Working Grp, ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net
doi: https://doi.org/10.1101/214494
Wei Jiao
1 Ontario Institute for Cancer Research;
Gurnit Atwal
2 University of Toronto;
Paz Polak
3 Icahn School of Medicine at Mount Sinai;
Rosa Karlic
4 University of Zagreb;
Edwin Cuppen
5 Hartwig Medical Foundation;
Alexandra Danyi
6 University Medical Center Utrecht;
Jeroen de Ridder
6 University Medical Center Utrecht;
Carla van Herpen
7 Radboud University Medical Center;
Martijn P Lolkema
7 Radboud University Medical Center;
Neeltje Steeghs
8 The Netherlands Cancer Institute;
Gad Getz
9 The Broad Institute of MIT and Harvard;
Quaid D Morris
2 University of Toronto;
Lincoln D. Stein
1 Ontario Institute for Cancer Research;
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Article usage
Posted January 22, 2019.
A deep learning system can accurately classify primary and metastatic cancers based on patterns of passenger mutations
Wei Jiao, Gurnit Atwal, Paz Polak, Rosa Karlic, Edwin Cuppen, Alexandra Danyi, Jeroen de Ridder, Carla van Herpen, Martijn P Lolkema, Neeltje Steeghs, Gad Getz, Quaid D Morris, Lincoln D. Stein, PCAWG Pathology & Clinical Correlates Working Grp, ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net
bioRxiv 214494; doi: https://doi.org/10.1101/214494
A deep learning system can accurately classify primary and metastatic cancers based on patterns of passenger mutations
Wei Jiao, Gurnit Atwal, Paz Polak, Rosa Karlic, Edwin Cuppen, Alexandra Danyi, Jeroen de Ridder, Carla van Herpen, Martijn P Lolkema, Neeltje Steeghs, Gad Getz, Quaid D Morris, Lincoln D. Stein, PCAWG Pathology & Clinical Correlates Working Grp, ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net
bioRxiv 214494; doi: https://doi.org/10.1101/214494
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