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Sriram Sankararaman
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2020 – today
- 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
Personalized mood prediction from patterns of behavior collected with smartphones. npj Digit. Medicine 7(1) (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 - 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) - 2022
- [j17]Leah Briscoe
Evaluating supervised and unsupervised background noise correction in human gut microbiome data. PLoS Comput. Biol. 18(2) (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
- [j16]Arunabha Majumdar
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
Advancing admixture graph estimation via maximum likelihood network orientation. Bioinform. 37(Supplement): 142-150 (2021) - [j14]Nadav Rakocz
Automated identification of clinical features from sparsely annotated 3-dimensional medical imaging. npj Digit. Medicine 4 (2021) - [j13]Ruth Johnson
Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits. PLoS Comput. Biol. 17(10) (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 - [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
- [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) - [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 - [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)
2010 – 2019
- 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
- [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) - [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 - 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
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
Fast and accurate inference of local ancestry in Latino populations. Bioinform. 28(10): 1359-1367 (2012) - [c2]Sriram Sankararaman, Jay Chen, Lakshminarayanan Subramanian, Venugopalan Ramasubramanian:
TrickleDNS: Bootstrapping DNS security using social trust. COMSNETS 2012: 1-10 - 2010
- [b1]Sriram Sankararaman:
Statistical models for analyzing human genetic variation. University of California, Berkeley, USA, 2010 - [j6]Sriram Sankararaman, Fei Sha, Jack F. Kirsch, Michael I. Jordan
Active site prediction using evolutionary and structural information. Bioinform. 26(5): 617-624 (2010)
2000 – 2009
- 2009
- [j5]Bogdan Pasaniuc
Inference of locus-specific ancestry in closely related populations. Bioinform. 25(12) (2009) - [j4]Ron Alterovitz, Aaron Arvey
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) - [c1]Sriram Sankararaman, Gad Kimmel, Eran Halperin, Michael I. Jordan
On the Inference of Ancestries in Admixed Populations. RECOMB 2008: 424-433 - 2004
- [j1]Sougata Mukherjea
Enhancing a biomedical information extraction system with dictionary mining and context disambiguation. IBM J. Res. Dev. 48(5-6): 693-702 (2004)
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last updated on 2024-10-07 21:12 CEST by the dblp team
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