lunes, 18 de noviembre de 2013

DriverDB: an exome sequencing database for... [Nucleic Acids Res. 2013] - PubMed - NCBI

DriverDB: an exome sequencing database for... [Nucleic Acids Res. 2013] - PubMed - NCBI

2013 Nov 7. [Epub ahead of print]

DriverDB: an exome sequencing database for cancer driver gene identification.

Source

Pediatric Neurosurgery, Department of Surgery, Cheng Hsin General Hospital, Taipei 11220, Taiwan, VGH-YM Genomic Research Center, National Yang-Ming University, Taipei 11221, Taiwan, Institute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, Taiwan, Information Technology Office, Taipei Veterans General Hospital, Taipei 11217, Taiwan, Institute of Microbiology and Immunology, National Yang-Ming University, Taipei 11221, Taiwan and Department of Education and Research, Taipei City Hospital, Taipei 10341, Taiwan.

Abstract

Exome sequencing (exome-seq) has aided in the discovery of a huge amount of mutations in cancers, yet challenges remain in converting oncogenomics data into information that is interpretable and accessible for clinical care. We constructed DriverDB (http://ngs.ym.edu.tw/driverdb/), a database which incorporates 6079 cases of exome-seq data, annotation databases (such as dbSNP, 1000 Genome and Cosmic) and published bioinformatics algorithms dedicated to driver gene/mutation identification. We provide two points of view, 'Cancer' and 'Gene', to help researchers to visualize the relationships between cancers and driver genes/mutations. The 'Cancer' section summarizes the calculated results of driver genes by eight computational methods for a specific cancer type/dataset and provides three levels of biological interpretation for realization of the relationships between driver genes. The 'Gene' section is designed to visualize the mutation information of a driver gene in five different aspects. Moreover, a 'Meta-Analysis' function is provided so researchers may identify driver genes in customer-defined samples. The novel driver genes/mutations identified hold potential for both basic research and biotech applications.

PMID:
24214964
[PubMed - as supplied by publisher]
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