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.
Guthrie VB et al. (2018) Molecular Biology and Evolution. msy036, https://doi.org/10.1093/molbev/msy036 [Epub ahead of print] Article
Douville C et al. (2018) Proc Natl Acad Sci U S A 115(8):1871-1876. Article
Bailey MH, Tokheim C, Porta-Pardo E et al. (2018). Cell. 173(2):371-385.e18. Article
Dr. Karchin promoted to Full Professor of Biomedical Engineering and Oncology.
Ph.D. student Collin Tokheim wins Martin and Carol Macht award for Young Investigator day at Hopkins Medicine.
Postdoc Violeta Beleva Guthrie's paper on network analysis of the functional impact of multiple adaptive mutations is published Mol. Biol. Evo.
Ph.D. student Collin Tokheim's paper on Driver Mutations in Cancer (co-first author with Matt Bailey and Eduard Porta-Pardo) is publisned in Cell.
CRAVAT/MuPIT tutorial workshop at American Society of Human Genetics annual meeting 2018 in San Diego, CA. Time and location TBD.