Enhancing a biomedical information extraction system with dictionary mining and context disambiguation. - Sougata Mukherjea; L. Venkata Subramaniam; Gaurav Chanda; Sriram Sankararaman; Ravi Kothari; Vishal S. Batra; Deo N. Bhardwaj; Biplav Srivastava (IBM J. Res. Dev., 2004)

On the Inference of Ancestries in Admixed Populations. - Sriram Sankararaman; Gad Kimmel; Eran Halperin; Michael I. Jordan (RECOMB, 2008)

INTREPID - INformation-theoretic TREe traversal for Protein functional site IDentification. - Sriram Sankararaman; Kimmen Sjölander (Bioinform., 2008)

Inference of locus-specific ancestry in closely related populations. - Bogdan Pasaniuc; Sriram Sankararaman; Gad Kimmel; Eran Halperin (Bioinform., 2009)

ResBoost: characterizing and predicting catalytic residues in enzymes. - Ron Alterovitz; Aaron Arvey; Sriram Sankararaman; Carolina Dallett; Yoav Freund; Kimmen Sjölander (BMC Bioinform., 2009)

INTREPID: a web server for prediction of functionally important residues by evolutionary analysis. - Sriram Sankararaman; Bryan Kolaczkowski; Kimmen Sjölander (Nucleic Acids Res., 2009)

Active site prediction using evolutionary and structural information. - Sriram Sankararaman; Fei Sha; Jack F. Kirsch; Michael I. Jordan; Kimmen Sjölander (Bioinform., 2010)

Statistical models for analyzing human genetic variation. - Sriram Sankararaman (2010)

TrickleDNS: Bootstrapping DNS security using social trust. - Sriram Sankararaman; Jay Chen; Lakshminarayanan Subramanian; Venugopalan Ramasubramanian (COMSNETS, 2012)

Fast and accurate inference of local ancestry in Latino populations. - Yael Baran; Bogdan Pasaniuc; Sriram Sankararaman; Dara G. Torgerson; Christopher Gignoux; Celeste Eng; William Rodriguez-Cintron; Rocio Chapela; Jean G. Ford; Pedro C. Avila; Jose Rodriguez-Santana; Esteban Gonzàlez Burchard; et al. (Bioinform., 2012)

Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation. - Bogdan Pasaniuc; Sriram Sankararaman; Dara G. Torgerson; Christopher Gignoux; Noah Zaitlen; Celeste Eng; William Rodriguez-Cintron; Rocio Chapela; Jean G. Ford; Pedro C. Avila; Jose Rodriguez-Santana; Gary K. Chen; et al. (Bioinform., 2013)

Inferring parental genomic ancestries using pooled semi-Markov processes. - James Y. Zou; Eran Halperin; Esteban Gonzàlez Burchard; Sriram Sankararaman (Bioinform., 2015)

Tensor Composition Analysis Detects Cell-Type Specific Associations in Epigenetic Studies. - Elior Rahmani; Regev Schweiger; Saharon Rosset; Sriram Sankararaman; Eran Halperin (RECOMB, 2018)

A Unifying Framework for Summary Statistic Imputation. - Yue Wu; Eleazar Eskin; Sriram Sankararaman (RECOMB, 2018)

A unifying framework for joint trait analysis under a non-infinitesimal model. - Ruth Johnson; Huwenbo Shi; Bogdan Pasaniuc; Sriram Sankararaman (Bioinform., 2018)

A scalable estimator of SNP heritability for biobank-scale data. - Yue Wu; Sriram Sankararaman (Bioinform., 2018)

Scalable Multi-component Linear Mixed Models with Application to SNP Heritability Estimation. - Ali Pazokitoroudi; Yue Wu; Kathryn S. Burch; Kangcheng Hou; Bogdan Pasaniuc; Sriram Sankararaman (RECOMB, 2019)

Fast Estimation of Genetic Correlation for Biobank-Scale Data. - Yue Wu; Anna Yaschenko; Mohammadreza Hajy Heydary; Sriram Sankararaman (RECOMB, 2019)

Explaining Groups of Points in Low-Dimensional Representations. - Gregory Plumb; Jonathan Terhorst; Sriram Sankararaman; Ameet Talwalkar (ICML, 2020)

A Scalable Method for Estimating the Regional Polygenicity of Complex Traits. - Ruth Johnson; Kathryn S. Burch; Kangcheng Hou; Mario Paciuc; Bogdan Pasaniuc; Sriram Sankararaman (RECOMB, 2020)

Marginal Contribution Feature Importance - an Axiomatic Approach for The Natural Case. - Amnon Catav; Boyang Fu; Jason Ernst; Sriram Sankararaman; Ran Gilad-Bachrach (CoRR, 2020)

A Unifying Framework for Imputing Summary Statistics in Genome-Wide Association Studies. - Yue Wu; Eleazar Eskin; Sriram Sankararaman (J. Comput. Biol., 2020)

CONTRA: Contrarian statistics for controlled variable selection. - Mukund Sudarshan; Aahlad Manas Puli; Lakshmi Subramanian; Sriram Sankararaman; Rajesh Ranganath (AISTATS, 2021)

Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data. - Amnon Catav; Boyang Fu; Yazeed Zoabi; Ahuva Weiss-Meilik; Noam Shomron; Jason Ernst; Sriram Sankararaman; Ran Gilad-Bachrach (ICML, 2021)

An Efficient Linear Mixed Model Framework for Meta-Analytic Association Studies Across Multiple Contexts. - Brandon Jew; Jiajin Li; Sriram Sankararaman; Jae Hoon Sul (WABI, 2021)

A two-step approach to testing overall effect of gene-environment interaction for multiple phenotypes. - Arunabha Majumdar; Kathryn S. Burch; Tanushree Haldar; Sriram Sankararaman; Bogdan Pasaniuc; W. James Gauderman; John S. Witte (Bioinform., 2021)

Advancing admixture graph estimation via maximum likelihood network orientation. - Erin K. Molloy; Arun Durvasula; Sriram Sankararaman (Bioinform., 2021)

Contrastive Mixup: Self- and Semi-Supervised learning for Tabular Domain. - Sajad Darabi; Shayan Fazeli; Ali Pazoki; Sriram Sankararaman; Majid Sarrafzadeh (CoRR, 2021)

Automated identification of clinical features from sparsely annotated 3-dimensional medical imaging. - Nadav Rakocz; Jeffrey N. Chiang; Muneeswar G. Nittala; Giulia Corradetti; Liran Tiosano; Swetha Velaga; Michael Thompson; Brian L. Hill; Sriram Sankararaman; Jonathan L. Haines; Margaret A. Pericak-Vance; Dwight Stambolian; et al. (npj Digit. Medicine, 2021)

Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits. - Ruth Johnson; Kathryn S. Burch; Kangcheng Hou; Mario Paciuc; Bogdan Pasaniuc; Sriram Sankararaman (PLoS Comput. Biol., 2021)

AutoComplete: Deep Learning-Based Phenotype Imputation for Large-Scale Biomedical Data. - Ulzee An; Na Cai; Andy Dahl; Sriram Sankararaman (RECOMB, 2022)

Tractable and Expressive Generative Models of Genetic Variation Data. - Meihua Dang; Anji Liu; Xinzhu Wei; Sriram Sankararaman; Guy Van den Broeck (RECOMB, 2022)

Evaluating supervised and unsupervised background noise correction in human gut microbiome data. - Leah Briscoe; Brunilda Balliu; Sriram Sankararaman; Eran Halperin; Nandita R. Garud (PLoS Comput. Biol., 2022)

dotears: Scalable, consistent DAG estimation using observational and interventional data. - Albert Xue; Jingyou Rao; Sriram Sankararaman; Harold Pimentel (CoRR, 2023)

A Scalable Adaptive Quadratic Kernel Method for Interpretable Epistasis Analysis in Complex Traits. - Boyang Fu; Prateek Anand; Aakarsh Anand; Joel Mefford; Sriram Sankararaman (RECOMB, 2024)

Scalable Summary Statistics-Based Heritability Estimation Method with Individual Genotype Level Accuracy. - Moonseong Jeong; Ali Pazokitoroudi; Zhengtong Liu; Sriram Sankararaman (RECOMB, 2024)

MANOCCA: a robust and computationally efficient test of covariance in high-dimension multivariate omics data. - Christophe Boetto; Arthur Frouin; Léo Henches; Antoine Auvergne; Yuka Suzuki; Etienne Patin; Marius Bredon; Alec Chiu; Milieu Interieur Consortium; Sriram Sankararaman; Noah Zaitlen; Sean P. Kennedy; et al. (Briefings Bioinform., 2024)

VISTA: an integrated framework for structural variant discovery. - Varuni Sarwal; Seungmo Lee; Jianzhi Yang; Sriram Sankararaman; Mark Chaisson; Eleazar Eskin; Serghei Mangul (Briefings Bioinform., 2024)

Personalized mood prediction from patterns of behavior collected with smartphones. - Brunilda Balliu; Chris Douglas; Darsol Seok; Liat Shenhav; Yue Wu; Doxa Chatzopoulou; William Kaiser; Victor Chen; Jennifer Kim; Sandeep Deverasetty; Inna Arnaudova; Robert Gibbons; et al. (npj Digit. Medicine, 2024)

CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data Imputation. - Aditya Gorla; Ryan Wang; Zhengtong Liu; Ulzee An; Sriram Sankararaman (CoRR, 2025)

Scientific Applications Leveraging Randomized Linear Algebra. - Vivak Patel; Daniel Adrian Maldonado; Maksim Melnichenko; Nathaniel Pritchard; Vishwas Rao; Elizaveta Rebrova; Sriram Sankararaman (CoRR, 2025)

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models. - Ulzee An; Moonseong Jeong; Simon A. Lee; Aditya Gorla; Yuzhe Yang; Sriram Sankararaman (CoRR, 2025)