Recurrent Alteration Analysis
Recurrent Alteration Analysis is a computational method in the molecular classification of tumors that identifies genomic alterations recurring across tumor samples to distinguish driver mutations from passenger events.
44
Publications
2.9K
Citations
1.6K
Authors
491
Institutions
Publications per year
2017–2026
18
44
Analyses of non-coding somatic drivers in 2,658 cancer whole genomes
Esther Rheinbay, Morten Muhlig Nielsen, Federico Abascal et al. · Nature · 2020 · 663 citations · Full text
Functional impact bias reveals cancer drivers
Abel González-Pérez, Núria López-Bigas · Nucleic Acids Research · 2012 · 363 citations · Full text
Life Sciences, Genetics, Oncology +14
The mutational landscape of phosphorylation signaling in cancer
Jüri Reimand, Omar Wagih, Gary D. Bader · Scientific Reports · 2013 · 173 citations · Full text
Medicine, Cancer Biology, Genetics +17
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491
Simon Fraser University
Burnaby, Canada
4 h-index
9 publications
2.5K citations

University of British Columbia
Vancouver, Canada
4 h-index
8 publications
595 citations

University of Toronto
Toronto, Canada
3 h-index
30 publications
16.6K citations
The University of Texas MD Anderson Cancer Center
Houston, United States
3 h-index
41 publications
24.4K citations
Harvard University
Cambridge, United States
3 h-index
48 publications
26.3K citations
Yale University
New Haven, United States
3 h-index
54 publications
32.2K citations
Massachusetts General Hospital
Boston, United States
3 h-index
40 publications
21K citations
RIKEN Center for Integrative Medical Sciences
Yokohama, Japan
3 h-index
36 publications
18.1K citations
1–8 of 491
5 publications · 171 citations
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2 publications · 84 citations
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2 publications · 53 citations
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2 publications · 76 citations
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2 publications · 78 citations
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