Identification and functional validation of oncogenic drivers are essential steps toward advancing cancer precision medicine. Here, we have presented a comprehensive analysis of the somatic genomic landscape of the widely used BRAFV600E- and NRASQ61K-driven mouse models of melanoma. By integrating the data with publically available genomic, epigenomic, and transcriptomic information from human clinical samples, we confirmed the importance of several genes and pathways previously implicated in human melanoma, including the tumor-suppressor genes phosphatase and tensin homolog (
Michael Olvedy, Julie C. Tisserand, Flavie Luciani, Bram Boeckx, Jasper Wouters, Sophie Lopez, Florian Rambow, Sara Aibar, Bernard Thienpont, Jasmine Barra, Corinna Köhler, Enrico Radaelli, Sophie Tartare-Deckert, Stein Aerts, Patrice Dubreuil, Joost J. van den Oord, Diether Lambrechts, Paulo De Sepulveda, Jean-Christophe Marine
Usage data is cumulative from November 2018 through November 2019.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.