Nature Communications (Jan 2020)
Interpreting pathways to discover cancer driver genes with Moonlight
- Antonio Colaprico,
- Catharina Olsen,
- Matthew H. Bailey,
- Gabriel J. Odom,
- Thilde Terkelsen,
- Tiago C. Silva,
- André V. Olsen,
- Laura Cantini,
- Andrei Zinovyev,
- Emmanuel Barillot,
- Houtan Noushmehr,
- Gloria Bertoli,
- Isabella Castiglioni,
- Claudia Cava,
- Gianluca Bontempi,
- Xi Steven Chen,
- Elena Papaleo
Affiliations
- Antonio Colaprico
- Interuniversity Institute of Bioinformatics in Brussels (IB)2
- Catharina Olsen
- Interuniversity Institute of Bioinformatics in Brussels (IB)2
- Matthew H. Bailey
- Division of Oncology, Department of Medicine, Washington University in St. Louis
- Gabriel J. Odom
- Department of Public Health Sciences, University of Miami, Miller School of Medicine
- Thilde Terkelsen
- Computational Biology Laboratory, and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center
- Tiago C. Silva
- Department of Public Health Sciences, University of Miami, Miller School of Medicine
- André V. Olsen
- Computational Biology Laboratory, and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center
- Laura Cantini
- Institut Curie
- Andrei Zinovyev
- Institut Curie
- Emmanuel Barillot
- Institut Curie
- Houtan Noushmehr
- Department of Genetics, Ribeirão Preto Medical School, University of Sao Paulo
- Gloria Bertoli
- Institute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR)
- Isabella Castiglioni
- Institute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR)
- Claudia Cava
- Institute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR)
- Gianluca Bontempi
- Interuniversity Institute of Bioinformatics in Brussels (IB)2
- Xi Steven Chen
- Department of Public Health Sciences, University of Miami, Miller School of Medicine
- Elena Papaleo
- Computational Biology Laboratory, and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center
- DOI
- https://doi.org/10.1038/s41467-019-13803-0
- Journal volume & issue
-
Vol. 11,
no. 1
pp. 1 – 17
Abstract
Identification of cancer driver genes, especially those that can act as tumour suppressors or oncogenes depending on context, remains a challenge. Here, the authors introduce Moonlight, a tool that integrates multi-omic data to address this challenge and identify numerous dual-role cancer genes.
