Computational analysis of genomic and clinical data to aid medical decision making.
In the new "post-genome" era of personalized medicine, many variants critical to disease susceptibilities, prognosis and drug sensitivities will be identified and increased numbers of people will undergo DNA sequencing. We are developing algorithms and tools intended to facilitate this process.
We develop computational models to interpret and predict the impact of individual variation in the genome, transcriptome, and proteome. The models are being applied to cancer genomics, unclassified variants in Mendelian disease genes, and complex disease genetics. In collaboration with clinicians, pathologists, and experimental biologists, we aim to make significant improvements in individualized medicine within the next five years.
Tokheim CJ et al. (2016) Proc Natl Acad Sci U S A Dec 13;113(50):14330-14335. ArticleMascia DL, Karchin R (2016) PLoS Computational Biology. 12(5):e1004725. Article
Cai B, et al. (June 2017) Human Mutation Article
CRAVAT/MuPIT web tools upgraded to version 5.0 with GRCh38 support. 9/11/2017
CRAVAT/MuPIT tutorial workshop at American Society of Human Genetics annual meeting 2017 in Orlando, FL 7:15am Orange Ballroom FG - Lower Level/Hilton Orlando Hotel 10/20/2017
Registration is open for Gordon Research Conference on Human Genetic Variation and Disease, chaired by Dr. Karchin to be held June 10-15, 2018