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
Masica DL, et al.Jan 2017 Journal of the American Medical Informatics Assoc. Article
Foundations of Computational Biology II course poster session on May 5.
May 15. Chris Douville and Noushin Niknafs receive doctoral degrees in Biomedical Engineering. Congratulations Chris and Noushin!
Welcome to new lab members Lily Zheng (Ph.D. student Human Genetics) and Melody Xiaoshin Shao (Ph.D. student Biomedical Engineering)!
Dr. Karchin will present keynote talk at New York University Department of Biology annual Genome Symposium on June 2.