Shilpa

Shilpa Kobren, PhD

Associate Director of Rare Disease Analysis
Biomedical Informatics Research Training Fellow, 2018-2019

Shilpa Nadimpalli Kobren earned her PhD in Computer Science from Princeton University, where she worked under the supervision of Dr. Mona Singh. Kobren's doctoral research focused on developing novel computational methods to detect and interpret protein interaction and cellular network perturbations across species, across healthy human individuals, and across individuals with disease. Kobren's current research leverages genome-scale sequencing and molecular data in the context of heterogeneous clinical data and electronic health record data to derive insights on the molecular mechanisms underlying rare, undiagnosed human diseases. 

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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