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.
Niknafs N, Guthrie VB, Naiman DQ, Karchin R (2015) PLoS Computational Biology 11(10):e1004416 Article
Masica DL, Sosnay PR, Raraigh KS, Cutting GR, Karchin R (2015) Human Mol. Genetics. 24(7):1908-17 Article
Douville C, Masica DL et al. Jan 2016 Article
HotMAPS algorithm paper "Exome-scale discovery of hotspot mutation regions in human cancer using 3D protein structure" by Tokheim et al. published in Cancer Research Apr 28, 2016.
Ph.D student Chris Douville presents poster "Within Sample Detection of Large Chromosomal Changes" at NHGRI's Research Training and Career Development Annual Meeting in Bethesda, Maryland.
Ph.D student Noushin Niknafs presents SCHISM poster at Cancer as an Evolving and Systemic Disease meeting at Memorial Sloan Kettering Cancer Center, NYC.
Dr. Karchin presents keynote at ISCB NGS 2016 Genome Annotation meeting, Barcelona, Spain.