I hold an M.S. in Bioinformatics and am a Senior Research Application Developer focused on designing, modernizing, and operating national‑scale, NIH‑funded genomics platforms that enable secure, reproducible genetic discovery for thousands of investigators across diverse biomedical domains. Over more than 13 years, I have led the modernization of large‑scale analysis pipelines using workflow‑driven architectures, containerized computing, and secure cloud infrastructure aligned with federal security and accessibility standards. As a full‑stack engineer, I translate emerging analytical methods into robust, production‑ready systems for national research consortia. I also contribute through manuscript and program review and have co‑authored 30+ peer‑reviewed publications, cited 2,300+ times (h‑index 18), with research spanning infectious disease, cancer, cardiometabolic and kidney disease, and maternal health, and publications in Nature, Cell Genomics, Nature Genetics, and The American Journal of Human Genetics.

• Statistical and population genetics
• GWAS and large-scale genomic analyses
• Genotype imputation and polygenic risk modeling
• Computational and cloud-based bioinformatics methods
• Translational genomics and precision medicine

• Cavalcante RG, Lee C, Welch RP, Patil S, et al. Broad-Enrich: functional interpretation of large sets of broad genomic regions. *Bioinformatics*. 2014;30(17):i393-i400.
• Chi X, Sartor MA, Lee S, Anurag M, Patil S, et al. Universal concept signature analysis: genome-wide quantification of new biological and pathological functions of genes and pathways. *Brief Bioinform*. 2020;21(5):1717–1732.
• Cavalcante RG, Patil S, Park Y, Rozek LS, Sartor MA. Integrating DNA methylation and hydroxymethylation data with the mint pipeline. *Cancer Res*. 2017;77(21):e27–e30.
• Cavalcante RG, Patil S, Weymouth TE, et al. ConceptMetab: exploring relationships among metabolite sets to identify links among biomedical concepts. *Bioinformatics*. 2016;32(10):1536–1543.
• Welch RP, Lee C, Imbriano PM, Patil S, et al. ChIP-Enrich: gene set enrichment testing for ChIP-seq data. *Nucleic Acids Res*. 2014;42(13):e105.
• Lee CT, Cavalcante RG, Lee C, Qin T, Patil S, et al. Poly-Enrich: count-based methods for gene set enrichment testing with genomic regions. *NAR Genomics Bioinform*. 2020;2(1):lqaa006.
• Lee C, Patil S, Sartor MA. RNA-Enrich: a cut-off free functional enrichment testing method for RNA-seq. *Bioinformatics*. 2016;32(7):1100–1102.
• Qin T, Lee CT, Li S, Cavalcante RG, et al. Comprehensive enhancer-target gene assignments improve gene set level interpretation. *Genome Biol*. 2022;23(1):105.
• Salvatore M, Gu T, Mack JA, Patil S, et al. A phenome-wide association study of COVID-19 outcomes by race using electronic health records. *J Clin Med*. 2021;10(7):1351.
• Fritsche LG, Patil S, Beesley LJ, et al. Cancer PRSweb: an online repository with polygenic risk scores. *Am J Hum Genet*. 2020;107(5):815–836.
• Clark DJ, Dhanasekaran SM, Petralia F, et al. Integrated proteogenomic characterization of clear cell renal cell carcinoma. *Cell*. 2020;180(1):207.
• Zawistowski M, Fritsche LG, Pandit A, Patil S, et al. The Michigan Genomics Initiative: a biobank linking genotypes and electronic clinical records. *Cell Genomics*. 2023;3(2).
• Ma Y, Patil S, Zhou X, Mukherjee B, Fritsche LG. ExPRSweb: An online repository with polygenic risk scores. *Am J Hum Genet*. 2022;109(10):1742–1760.
• Ågren R, Patil S, Zhou X, et al. Major genetic risk factors for Dupuytren's disease are inherited from Neandertals. *Mol Biol Evol*. 2023;40(6):msad130.
• Forsgård RA, Rode J, Lobenius-Palmér K, et al. L. reuteri DSM 17938 supplementation and SARS-CoV-2 antibody response. *Gut Microbes*. 2023;15(1):2229938.
• Fadl HE, Patil S, Wikström AK, et al. Association of GDM risk factors with diagnosis and treatment. *Diabetes*. 2022;71(Suppl_1).
• de Brun M, Magnuson A, Montgomery S, Patil S, et al. Changing diagnostic criteria for gestational diabetes in Sweden. *PLoS Med*. 2024;21(7):e1004420.
• Elmasri AF, Park JM, Fitzgerald L, Patil S, et al. Impact of CYP3A5 genotype and cystic fibrosis on tacrolimus exposure. *Pharmacogenet Genomics*. 2023;33(8):199–200.
• Vanderwerff B, Bertucci-Richter E, Patil S, et al. Expanding biobank pharmacogenomics using machine learning. *Genetics*. 2025;iyaf088.
• Friedman RK, Heath AS, Huffman JE, et al. Genetic study of von Willebrand factor antigen and VWD risk. *J Thromb Haemost*. 2025.

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