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ORCIDSriram Sankararaman
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Books and Theses
- 2010
[b1]Sriram Sankararaman:
Statistical models for analyzing human genetic variation. University of California, Berkeley, USA, 2010
Journal Articles
- 2024
- [j19]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, Lluis Quintana-Murci, Darragh Duffy, Harry Sokol, Hugues Aschard:
MANOCCA: a robust and computationally efficient test of covariance in high-dimension multivariate omics data. Briefings Bioinform. 25(4) (2024) - [j18]Brunilda Balliu, Chris Douglas, Darsol Seok, Liat Shenhav, Yue Wu, Doxa Chatzopoulou, William Kaiser, Victor Chen, Jennifer Kim, Sandeep Deverasetty, Inna Arnaudova, Robert Gibbons, Eliza Congdon, Michelle G. Craske, Nelson B. Freimer, Eran Halperin, Sriram Sankararaman, Jonathan Flint:
Personalized mood prediction from patterns of behavior collected with smartphones. npj Digit. Medicine 7(1) (2024) - 2022
- [j17]Leah Briscoe, Brunilda Balliu, Sriram Sankararaman, Eran Halperin, Nandita R. Garud:
Evaluating supervised and unsupervised background noise correction in human gut microbiome data. PLoS Comput. Biol. 18(2) (2022) - 2021
- [j16]Arunabha Majumdar, Kathryn S. Burch, Tanushree Haldar, Sriram Sankararaman, Bogdan Pasaniuc, W. James Gauderman, John S. Witte:
A two-step approach to testing overall effect of gene-environment interaction for multiple phenotypes. Bioinform. 36(24): 5640-5648 (2021) - [j15]Erin K. Molloy, Arun Durvasula, Sriram Sankararaman:
Advancing admixture graph estimation via maximum likelihood network orientation. Bioinform. 37(Supplement): 142-150 (2021) - [j14]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, Srinivas R. Sadda, Eran Halperin:
Automated identification of clinical features from sparsely annotated 3-dimensional medical imaging. npj Digit. Medicine 4 (2021) - [j13]Ruth Johnson, Kathryn S. Burch, Kangcheng Hou, Mario Paciuc, Bogdan Pasaniuc, Sriram Sankararaman:
Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits. PLoS Comput. Biol. 17(10) (2021) - 2020
- [j12]Yue Wu, Eleazar Eskin, Sriram Sankararaman:
A Unifying Framework for Imputing Summary Statistics in Genome-Wide Association Studies. J. Comput. Biol. 27(3): 418-428 (2020) - 2018
- [j11]Yue Wu, Sriram Sankararaman:
A scalable estimator of SNP heritability for biobank-scale data. Bioinform. 34(13): i187-i194 (2018) - [j10]Ruth Johnson, Huwenbo Shi, Bogdan Pasaniuc, Sriram Sankararaman:
A unifying framework for joint trait analysis under a non-infinitesimal model. Bioinform. 34(13): i195-i201 (2018) - 2015
- [j9]James Y. Zou, Eran Halperin, Esteban Gonzàlez Burchard, Sriram Sankararaman:
Inferring parental genomic ancestries using pooled semi-Markov processes. Bioinform. 31(12): 190-196 (2015) - 2013
- [j8]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, Loic Le Marchand, Brian E. Henderson, David Reich, Christopher A. Haiman, Esteban Gonzàlez Burchard, Eran Halperin:
Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation. Bioinform. 29(11): 1407-1415 (2013) - 2012
- [j7]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, Eran Halperin:
Fast and accurate inference of local ancestry in Latino populations. Bioinform. 28(10): 1359-1367 (2012) - 2010
- [j6]Sriram Sankararaman, Fei Sha, Jack F. Kirsch, Michael I. Jordan, Kimmen Sjölander:
Active site prediction using evolutionary and structural information. Bioinform. 26(5): 617-624 (2010) - 2009
- [j5]Bogdan Pasaniuc, Sriram Sankararaman, Gad Kimmel, Eran Halperin:
Inference of locus-specific ancestry in closely related populations. Bioinform. 25(12) (2009) - [j4]Ron Alterovitz, Aaron Arvey, Sriram Sankararaman, Carolina Dallett, Yoav Freund, Kimmen Sjölander:
ResBoost: characterizing and predicting catalytic residues in enzymes. BMC Bioinform. 10 (2009) - [j3]Sriram Sankararaman, Bryan Kolaczkowski, Kimmen Sjölander:
INTREPID: a web server for prediction of functionally important residues by evolutionary analysis. Nucleic Acids Res. 37(Web-Server-Issue): 390-395 (2009) - 2008
- [j2]Sriram Sankararaman, Kimmen Sjölander:
INTREPID - INformation-theoretic TREe traversal for Protein functional site IDentification. Bioinform. 24(21): 2445-2452 (2008) - 2004
- [j1]Sougata Mukherjea, L. Venkata Subramaniam, Gaurav Chanda, Sriram Sankararaman, Ravi Kothari, Vishal S. Batra, Deo N. Bhardwaj, Biplav Srivastava:
Enhancing a biomedical information extraction system with dictionary mining and context disambiguation. IBM J. Res. Dev. 48(5-6): 693-702 (2004)
Conference and Workshop Papers
- 2024
- [c15]Boyang Fu, Prateek Anand, Aakarsh Anand, Joel Mefford, Sriram Sankararaman:
A Scalable Adaptive Quadratic Kernel Method for Interpretable Epistasis Analysis in Complex Traits. RECOMB 2024: 458-461 - [c14]Moonseong Jeong, Ali Pazokitoroudi, Zhengtong Liu, Sriram Sankararaman:
Scalable Summary Statistics-Based Heritability Estimation Method with Individual Genotype Level Accuracy. RECOMB 2024: 475-478 - 2022
- [c13]Meihua Dang, Anji Liu, Xinzhu Wei, Sriram Sankararaman, Guy Van den Broeck:
Tractable and Expressive Generative Models of Genetic Variation Data. RECOMB 2022: 356-357 - [c12]Ulzee An, Na Cai, Andy Dahl, Sriram Sankararaman:
AutoComplete: Deep Learning-Based Phenotype Imputation for Large-Scale Biomedical Data. RECOMB 2022: 385-386 - 2021
- [c11]Mukund Sudarshan, Aahlad Manas Puli, Lakshmi Subramanian, Sriram Sankararaman, Rajesh Ranganath:
CONTRA: Contrarian statistics for controlled variable selection. AISTATS 2021: 1900-1908 - [c10]Amnon Catav, Boyang Fu, Yazeed Zoabi, Ahuva Weiss-Meilik, Noam Shomron, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach:
Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data. ICML 2021: 1324-1335 - [c9]Brandon Jew, Jiajin Li, Sriram Sankararaman, Jae Hoon Sul:
An Efficient Linear Mixed Model Framework for Meta-Analytic Association Studies Across Multiple Contexts. WABI 2021: 10:1-10:17 - 2020
- [c8]Gregory Plumb, Jonathan Terhorst, Sriram Sankararaman, Ameet Talwalkar:
Explaining Groups of Points in Low-Dimensional Representations. ICML 2020: 7762-7771 - [c7]Ruth Johnson, Kathryn S. Burch, Kangcheng Hou, Mario Paciuc, Bogdan Pasaniuc, Sriram Sankararaman:
A Scalable Method for Estimating the Regional Polygenicity of Complex Traits. RECOMB 2020: 253-254 - 2019
- [c6]Ali Pazokitoroudi, Yue Wu, Kathryn S. Burch, Kangcheng Hou, Bogdan Pasaniuc, Sriram Sankararaman:
Scalable Multi-component Linear Mixed Models with Application to SNP Heritability Estimation. RECOMB 2019: 312-313 - [c5]Yue Wu, Anna Yaschenko, Mohammadreza Hajy Heydary, Sriram Sankararaman:
Fast Estimation of Genetic Correlation for Biobank-Scale Data. RECOMB 2019: 322-323 - 2018
- [c4]Elior Rahmani, Regev Schweiger, Saharon Rosset, Sriram Sankararaman, Eran Halperin:
Tensor Composition Analysis Detects Cell-Type Specific Associations in Epigenetic Studies. RECOMB 2018: 274-275 - [c3]Yue Wu, Eleazar Eskin, Sriram Sankararaman:
A Unifying Framework for Summary Statistic Imputation. RECOMB 2018: 289-290 - 2012
- [c2]Sriram Sankararaman, Jay Chen, Lakshminarayanan Subramanian, Venugopalan Ramasubramanian:
TrickleDNS: Bootstrapping DNS security using social trust. COMSNETS 2012: 1-10 - 2008
- [c1]Sriram Sankararaman, Gad Kimmel, Eran Halperin, Michael I. Jordan:
On the Inference of Ancestries in Admixed Populations. RECOMB 2008: 424-433
Informal and Other Publications
- 2023
- [i4]Albert Xue, Jingyou Rao, Sriram Sankararaman, Harold Pimentel:
dotears: Scalable, consistent DAG estimation using observational and interventional data. CoRR abs/2305.19215 (2023) - 2021
- [i3]Sajad Darabi, Shayan Fazeli, Ali Pazoki, Sriram Sankararaman, Majid Sarrafzadeh:
Contrastive Mixup: Self- and Semi-Supervised learning for Tabular Domain. CoRR abs/2108.12296 (2021) - 2020
- [i2]Gregory Plumb, Jonathan Terhorst, Sriram Sankararaman, Ameet Talwalkar:
Explaining Groups of Points in Low-Dimensional Representations. CoRR abs/2003.01640 (2020) - [i1]Amnon Catav, Boyang Fu, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach:
Marginal Contribution Feature Importance - an Axiomatic Approach for The Natural Case. CoRR abs/2010.07910 (2020)
Coauthor Index
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