Chirag Patel, PhD
Associate Professor of Biomedical Informatics
Chirag Patel's long-term research goal is to address problems in human health and disease by developing computational and bioinformatics methods to reproducibly and efficiently reason over high-throughput data streams spanning molecules to populations. Patel's group aims to dissect inter-individual differences in human phenomes through strategies that integrate data sources that capture the comprehensive clinical experience (e.g., through the electronic medical record), the complex phenomena of environmental exposure (e.g., high-throughput measures of the exposome), and inherited genomic variation. He received his doctorate in biomedical informatics from Stanford University.
DBMI Research Areas
DBMI Courses
- BMI 704 - Data Science I: Data Science for Medical Decision Making
- BMI 722 - Topics in Translational Biomedical Informatics
Career Opportunities
Systematic assessment of pharmaceutical prescriptions in association with cancer risk: a method to conduct a population-wide medication-wide longitudinal study.
Authors: Patel CJ, Ji J, Sundquist J, Ioannidis JP, Sundquist K.
Sci Rep
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Sci Rep
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Environment-Wide Association Study of Blood Pressure in the National Health and Nutrition Examination Survey (1999-2012).
Comparative analyses of population-scale phenomic data in electronic medical records reveal race-specific disease networks.
Authors: Glicksberg BS, Li L, Badgeley MA, Shameer K, Kosoy R, Beckmann ND, Pho N, Hakenberg J, Ma M, Ayers KL, Hoffman GE, Dan Li S, Schadt EE, Patel CJ, Chen R, Dudley JT.
Bioinformatics
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Bioinformatics
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Mendelian randomization study of adiposity-related traits and risk of breast, ovarian, prostate, lung and colorectal cancer.
Authors: Gao C, Patel CJ, Michailidou K, Peters U, Gong J, Schildkraut J, Schumacher FR, Zheng W, Boffetta P, Stucker I, Willett W, Gruber S, Easton DF, Hunter DJ, Sellers TA, Haiman C, Henderson BE, Hung RJ, Amos C, Pierce BL, Lindström S, Kraft P.
Int J Epidemiol
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Int J Epidemiol
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Analytical Complexity in Detection of Gene Variant-by-Environment Exposure Interactions in High-Throughput Genomic and Exposomic Research.
Field-wide meta-analyses of observational associations can map selective availability of risk factors and the impact of model specifications.
Authors: Serghiou S, Patel CJ, Tan YY, Koay P, Ioannidis JP.
J Clin Epidemiol
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J Clin Epidemiol
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ksRepo: a generalized platform for computational drug repositioning.
REPRODUCIBLE AND SHAREABLE QUANTIFICATIONS OF PATHOGENICITY.
METHODS TO ENHANCE THE REPRODUCIBILITY OF PRECISION MEDICINE.
Authors: Manrai AK, Patel CJ, Gehlenborg N, Tatonetti NP, Ioannidis JP, Kohane IS.
Pac Symp Biocomput
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Pac Symp Biocomput
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Nutrient-wide association study of 57 foods/nutrients and epithelial ovarian cancer in the European Prospective Investigation into Cancer and Nutrition study and the Netherlands Cohort Study.
Authors: Merritt MA, Tzoulaki I, van den Brandt PA, Schouten LJ, Tsilidis KK, Weiderpass E, Patel CJ, Tjønneland A, Hansen L, Overvad K, His M, Dartois L, Boutron-Ruault MC, Fortner RT, Kaaks R, Aleksandrova K, Boeing H, Trichopoulou A, Lagiou P, Bamia C, Palli D, Krogh V, Tumino R, Ricceri F, Mattiello A, Bueno-de-Mesquita HB, Onland-Moret NC, Peeters PH, Skeie G, Jareid M, Quirós JR, Obón-Santacana M, Sánchez MJ, Chamosa S, Huerta JM, Barricarte A, Dias JA, Sonestedt E, Idahl A, Lundin E, Wareham NJ, Khaw KT, Travis RC, Ferrari P, Riboli E, Gunter MJ.
Am J Clin Nutr
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Am J Clin Nutr
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