BUSCADOR RECOLECTA

The cancer bioMarkers database is curated and maintained by several clinical and scientific experts in the field of precision oncology supported by the European Union’s Horizon 2020 funding. This database is currently being integrated with knowledge databases of other institutions in a collaborative effort of the Global Alliance for Genomics and Health.

A tool aimed at the rational design of cancer gene panels. It estimates the cost-effectiveness of the designed panel on a cohort of tumors and provides reports on the importance of individual mutations for tumorigenesis or therapy.

Machine-learning based approach to classify cancer driver genes into to Activating or Loss of Function roles for cancer gene development.

This database contains information on the genes identified as drivers in Rubio-Perez and Tamborero et al. (2015). It contains information on driver identification at mutational, CNA and gene fusion level. Additional ancillary information about the role and major clonality of drivers is also included. A table is also provided with the list of datasets used for mutational driver identification.

Bioinformatics method to identify individual driver mutations.

This database contains the results of the driver analysis performed by the Cancer Genome Interpreter across 6,792 exomes of a pan-cancer cohort of 28 tumor types. Validated oncogenic mutations are identified according to the state-of-the-art clinical and experimental data, whereas the effect of the mutations of unknown significance is predicted by the OncodriveMUT method.

CGI drug prescription assigns targeted drugs to a tumor, based on its genomic alterations, according different levels of evidence (from pre-clinical assays to clinical guidelines).