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Nat Methods. 2015 Jul;12(7):615-621. doi: 10.1038/nmeth.3440.

Pathway and network analysis of cancer genomes.

Author information

1
Cellular Signal Integration Group (C-SIG), Technical University of Denmark, Lyngby, Denmark.
2
The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada.
3
Informatics and Biocomputing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
4
Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA.
5
Division of Cancer Genomics, National Cancer Center, Chuo-ku, Tokyo, Japan.
6
Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain.
7
Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
8
Research Unit on Biomedical Informatics, University Pompeu Fabra, Barcelona, Spain.
9
Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St. Lucia, Brisbane, Queensland, Australia.
10
Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.
11
Department of Computer Science and Center for Computational Molecular Biology, Brown University, Providence, RI, USA.
12
Department of Systems Biology, Harvard Medical School, Boston, MA USA.
13
Department of Cell and Systems Biology, University of Toronto, Toronto, Ontario, Canada.
14
Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
15
Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada.
16
Department of Biomolecular Engineering, University of California, Santa Cruz, California, USA.
17
Center for Biomolecular Science and Engineering, University of California, Santa Cruz, California, USA.
18
Biotech Research & Innovation Centre (BRIC), University of Copenhagen (UCPH), DK-2200 Copenhagen, Denmark.
19
Instituci├│ Catalana de Recerca i Estudis Avan├žats, Barcelona, Spain.
20
Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
#
Contributed equally

Abstract

Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations.

PMID:
26125594
PMCID:
PMC4717906
DOI:
10.1038/nmeth.3440
[Indexed for MEDLINE]
Free PMC Article

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