Shilpa Kobren

Shilpa Kobren

Associate Director of Rare Disease Analysis

Shilpa Kobren's research centers around developing computational methods to analyze genome sequencing data in the context of other ‘omics and clinical data to prioritize and functionally interpret genetic variants with roles in human disease. She focuses primarily on uncovering elusive genetic underpinnings of health conditions such as cancer, Mendelian disorders, and unexpected treatment responders. Pinpointing disease-relevant genetic variants that defy detection can shine a light on the limits of our biological and medical knowledge and requires the development of computationally tractable and interpretable models that integrate high-throughput functionality data, population-level 'omics data, and patient health data.

She chairs the bioinformatics working group in the Undiagnosed Diseases Network, teaches about genome sequencing analysis for rare disease diagnosis, and mentors and advises undergraduate, Master's, and PhD students on their research projects.

Polygenic risk scores for autoimmune related diseases are significantly different in cancer exceptional responders.
Authors: Chen S, Tan ALM, Saad Menezes MC, Mao JF, Perry CL, Vella ME, Viswanadham VV, Kobren S, Churchill S, Kohane IS.
NPJ Precis Oncol
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VarPPUD: Variant post prioritization developed for undiagnosed genetic disorders.
Authors: Yin R, Gutierrez A, Kobren SN, Avillach P.
medRxiv
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Phenotypic overlap between rare disease patients and variant carriers in a large population cohort informs biological mechanisms.
Authors: Fitzsimmons L, Beaulieu-Jones B, Kobren SN.
medRxiv
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Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations.
Authors: Nadimpalli Kobren S, Moldovan MA, Reimers R, Traviglia D, Li X, Barnum D, Veit A, Willett J, Berselli M, Ronchetti W, Sherwood R, Krier J, Kohane IS, Sunyaev SR.
bioRxiv
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RExPRT: a machine learning tool to predict pathogenicity of tandem repeat loci.
Authors: Fazal S, Danzi MC, Xu I, Kobren SN, Sunyaev S, Reuter C, Marwaha S, Wheeler M, Dolzhenko E, Lucas F, Wuchty S, Tekin M, Züchner S, Aguiar-Pulido V.
Genome Biol
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Simulation of undiagnosed patients with novel genetic conditions.
Authors: Alsentzer E, Finlayson SG, Li MM, Kobren SN, Kohane IS.
Nat Commun
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The contribution of mosaicism to genetic diseases and de novo pathogenic variants.
Authors: Tinker RJ, Bastarache L, Ezell K, Kobren SN, Esteves C, Rosenfeld JA, Macnamara EF, Hamid R, Cogan JD, Rinker D, Mukharjee S, Glass I, Dipple K, Phillips JA.
Am J Med Genet A
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Commonalities across computational workflows for uncovering explanatory variants in undiagnosed cases.
Authors: Kobren SN, Baldridge D, Velinder M, Krier JB, LeBlanc K, Esteves C, Pusey BN, Züchner S, Blue E, Lee H, Huang A, Bastarache L, Bican A, Cogan J, Marwaha S, Alkelai A, Murdock DR, Liu P, Wegner DJ, Paul AJ, Sunyaev SR, Kohane IS.
Genet Med
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Innovative methodological approaches for data integration to derive patterns across diverse, large-scale biomedical datasets.
Authors: Beaulieu-Jones B, Darabos C, Kim D, Verma A, Kobren SN.
Pac Symp Biocomput
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PertInInt: An Integrative, Analytical Approach to Rapidly Uncover Cancer Driver Genes with Perturbed Interactions and Functionalities.
Authors: Kobren SN, Chazelle B, Singh M.
Cell Syst
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