Preprints and Unpublished Work
Vladimir Feinberg, Li-Fang Cheng, Kai Li, Barbara E Engelhardt. Large linear multi-output Gaussian process learning for time series, arXiv preprint arXiv:1705.10813. [bibtex] [pdf]
Ashlee Valente, Geoffrey Ginsburg, Barbara E. Engelhardt. Nonparametric reduced-rank regression for multi-SNP, multi-trait association mapping, arXiv preprint arXiv:1512.02306. [bibtex] [pdf]
Mehmet E Basbug, Barbara E Engelhardt. Clustering with beta divergences, arXiv preprint arXiv:1510.05491. [bibtex] [pdf]
Mehmet E Basbug, Barbara E Engelhardt. Coupled compound Poisson factorization, arXiv preprint arXiv:1701.02058. [bibtex] [pdf]
Barbara E Engelhardt, Ryan P Adams. Bayesian structured sparsity from Gaussian fields, arXiv preprint arXiv:1407.2235, 1. [bibtex] [pdf]
Bianca Dumitrascu, Karen Feng, Barbara E. Engelhardt. GT-TS: Experimental design for maximizing cell type discovery in single-cell data, bioRxiv: 386540. [bibtex] [pdf]
Bianca Dumitrascu, Soledad Villar, Dustin G. Mixon, Barbara E. Engelhardt. Optimal marker gene selection for cell type discrimination in single cell analyses, bioRxiv:599654. [bibtex] [pdf]
Jonathan Lu, Bianca Dumitrascu, Ian C. McDowell, Alejandro Barrera, Hong Linda K., Sarah M. Leichter, Timothy E. Reddy, Barbara E. Engelhardt. Causal network inference from gene transcriptional time series response to glucocorticoids, bioRxiv:587170. [bibtex] [pdf]
Li-Fang Cheng, Bianca Dumitrascu, Michael Minyi Zhang, Corey Chivers, Michael E. Draugelis, Kai Li, Barbara E. Engelhardt. Patient-specific effects of medication using latent force models with Gaussian processes, arXiv preprint arXiv:1906.00226. [bibtex] [pdf]
Li-Fang Cheng, Gregory Darnell, Corey Chivers, Michael E. Draugelis, Kai Li, Barbara E. Engelhardt. Sparse multi-output Gaussian processes for medical time series prediction, arXiv preprint arXiv:1703.09112. [bibtex] [pdf]
Michael Minyi Zhang, Bianca Dumitrascu, Sinead A. Williamson, Barbara E. Engelhardt. Sequential Gaussian processes for online learning of nonstationary functions, arXiv preprint arXiv:1905.10003. [bibtex] [pdf]
Niranjani Prasad, Barbara E. Engelhardt, Finale Doshi-Velez. Defining admissible rewards for high confidence policy evaluation, arXiv preprint arXiv:1905.13167. [bibtex] [pdf]
Archit Verma, Barbara E. Engelhardt. A robust nonlinear low-dimensional manifold for single cell RNA-seq data, bioRxiv:443044. [bibtex] [pdf]
Gautam Sabnis, Debdeep Pati, Barbara E Engelhardt, Natesh Pillai. A divide and conquer strategy for high dimensional Bayesian factor models, arXiv preprint arXiv:1612.02875. [bibtex] [pdf]
Ian C McDowell, Athma A Pai, Cong Guo, Christopher M Vockley, Christopher D Brown, Tim E Reddy, Barbara E Engelhardt. Many long intergenic non-coding RNAs distally regulate mRNA gene expression levels, bioRXiv preprint 044719. [bibtex] [pdf]
Brian Jo, Yuan He, Benjamin J. Strober, Princy Parsana, Francois Aguet, Andrew A. Brown, Stephane E Castel, Eric R. Gamazon, Ariel Gewirtz, Genna Gliner, Buhm Han, Amy Z. He, Eun Yong Kang, Ian C. McDowell, Xiao Li, Pejman Mohammadi, Christine B. Peterson, Gerald Quon, Ashis Saha, Ayellet V. Segré, Jae Hoon Sul, Timothy J. Sullivan, Kristin G. Ardlie, Christopher D. Brown, Donald F. Conrad, Nancy J. Cox, Emmanouil T. Dermitzakis, Eleazar Eskin, Manolis Kellis, Tuuli Lappalainen, Chiara Sabatti, GTEx Consortium, Barbara E. Engelhardt*, Alexis Battle*. Distant regulatory effects of genetic variation in multiple human tissues, bioRXiv preprint 074419. [bibtex] [pdf]
Chuan Gao, Christopher D Brown, Barbara E Engelhardt. A latent factor model with a mixture of sparse and dense factors to model gene expression data affected by technical and biological covariates, arXiv preprint arXiv:1310.4792. [bibtex] [pdf]
Jordan T Ash, Barbara E Engelhardt, Robert E Schapire. Unsupervised domain adaptation using approximate label matching, arXiv preprint arXiv:1602.04889v3. [bibtex] [pdf]
Refereed Articles
Gregory Gundersen, Bianca Dumitrascu, Barbara E. Engelhardt.End-to-end training of deep probabilistic CCA on paired biomedical observations, in Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2019. [bibtex]
Grace Guan, Barbara E. Engelhardt.Predicting sick patient volume in a pediatric outpatient setting using time series analysis, Proceedings of Machine Learning for Health Care (MLHC; accepted), 2019. [bibtex]
Rebecca Elyanow, Bianca Dumitrascu, Barbara E. Engelhardt, Benjamin J. Raphael. netNMF-sc: Leveraging gene-gene interactions for imputation and dimensionality reduction in single-cell expression analysis, Proceedings of the 23rd International Conference on Research in Computational Molecular Biology (RECOMB), 2019. [bibtex] [pdf]
Li-Fang Cheng, Niranjani Prasad, Barbara E. Engelhardt. An optimal policy for patient laboratory tests in intensive care units, Proceedings of the Pacific Symposium on Biocomputing (PSB), 2019. [bibtex] [pdf]
Jordan Ash*, Gregory Darnell*, Daniel Munro*, Barbara E. Engelhardt. Joint analysis of gene expression levels and histological images identifies genes associated with tissue morphology, Nature Communications (accepted), 2019. [bibtex] [pdf]
Derek Aguiar, Li-Fang Cheng, Bianca Dumitrascu, Fantine Mordelet, Athma A. Pai, Barbara E. Engelhardt. BIISQ: Bayesian nonparametric discovery of Isoforms and Individual Specific Quantification, Nature Communications, 9(1681), 2018. [bibtex] [pdf]
Ian C. McDowell, Alejandro Barrero, Anthony M. D’Ippolito, Christopher M. Vockley, Linda K. Hong, Sarah M. Leichter, Luke C. Bartelt, William H. Majoros, Lingyun Song, Alexias Safi, D. Dewran Ko├žak, Charles A. Gersbach, Alexander J. Hartemink, Gregory E. Crawford, Barbara E. Engelhardt, Timothy E. Reddy. Glucocorticoid receptor recruits to enhancers and drives activation by motif-directed binding, Genome Research, 2018. [bibtex] [pdf]
Ian C. McDowell, Dinesh Manandhar, Christopher M. Vockley, Amy Schmid, Timothy E. Reddy*, Barbara E. Engelhardt*. Clustering gene expression time series data using an infinite Gaussian process mixture model, PLoS Computational Biology, 14(1):e1005896, 2018. [bibtex] [pdf]
Bianca Dumitrascu, Gregory Darnell, Julien Ayroles, Barbara E Engelhardt. A Bayesian test to identify variance effects, Bioinformatics, 2018. [bibtex] [pdf]
Bianca Dumitrascu*, Karen Feng*, Barbara E. Engelhardt. PG-TS: Improved Thompson sampling for logistic contextual bandits, Proceedings of Neural Information Processing Systems (NeurIPS), 2018. [bibtex] [pdf]
Allison J.B. Chaney, Brandon M. Stewart, Barbara E. Engelhardt. How algorithmic confounding in recommendation systems increases homogeneity and decreases utility, 12th ACM Conference on Recommender Systems, 2018. [bibtex] [pdf]
Ghassen Jerfel, Mehmet E Basbug, Barbara E Engelhardt. Dynamic collaborative filtering with compound Poisson factorization, Proceedings of the Artificial Intelligence and Statistics (AISTATS) Conference, 54, 2017. [bibtex] [pdf]
Shiwen Zhao, Barbara E Engelhardt, Sayan Mukherjee, David B Dunson. Fast moment estimation for generalized latent Dirichlet models, Journal of the American Statistical Association (JASA), 2017. [bibtex] [pdf]
Sanvesh Srivastava, Barbara E Engelhardt, David B Dunson. Expandable factor analysis, Biometrika, 2017. [bibtex] [pdf]
Ashis Saha, Yungil Kim*, Ariel D. H. Gewirtz*, Brian Jo, Chuan Gao, Ian C. McDowell, GTEx Consortium, Barbara E. Engelhardt*, Alexis Battle*. Co-expression networks reveal the tissue-specific regulation of transcription and splicing, Genome Research, 27(11):1843–1858, 2017. [bibtex] [pdf]
Niranjani Prasad, Li-Fang Cheng, Corey Chivers, Michael Draugelis, Barbara E Engelhardt. A reinforcement learning approach to weaning of mechanical ventilation in intensive care units, Proceedings of Uncertainty in Artificial Intelligence (UAI), 2017. [bibtex] [pdf]
GTEx Consortium, Alexis Battle*, Christopher D. Brown*, Barbara E. Engelhardt*, Stephen M. Montgomery*. Genetic effects on gene expression across human tissues, Nature, 550, 2017. [bibtex] [pdf]
Gregory Darnell, Stoyan Georgiev, Sayan Mukherjee, Barbara E Engelhardt. Adaptive randomized dimension reduction on massive data, Journal of Machine Learning Research (JMLR), 18(140):1-30, 2017. [bibtex] [pdf]
Jonathan D Cohen, Nathaniel Daw, Barbara Engelhardt, Uri Hasson, Kai Li, Yael Niv, Kenneth A Norman, Jonathan Pillow, Peter J Ramadge, Nicholas B Turk-Browne, Theodore L Willke. Computational approaches to fMRI analysis, Nature Neuroscience, Nature Research, 20(3):304–313, 2017. [bibtex] [pdf]
Mehmet E Basbug, Barbara E Engelhardt. Hierarchical compound Poisson factorization, Proceedings of the International Conference on Machine Learning, 2016. [bibtex] [pdf]
Shiwen Zhao, Chuan Gao, Sayan Mukherjee, Barbara E Engelhardt. Bayesian group latent factor analysis with structured sparse priors, Journal of Machine Learning Research (JMLR), 2016. [bibtex] [pdf]
Peter D Tonner, Cynthia D Darnell, Barbara E Engelhardt, Amy Schmid. Detecting differential growth of microbial populations with Gaussian process regression, Genome Research, 27, 2016. [bibtex] [pdf]
Chuan Gao, Shiwen Zhao, Ian C McDowell, Christopher D Brown, Barbara E Engelhardt. Context-specific and differential gene co-expression networks via Bayesian biclustering models, PLOS Computational Biology, 12, 2016. [bibtex] [pdf]
Genetics of Personality Consortium. Meta-analysis of genome-wide association studies for neuroticism, and the polygenic association with major depressive disorder, JAMA Psychiatry, 72(7):642-650, 2015. [bibtex] [pdf] [doi]
Weiwei Zhang, Tim Spector, Panos Deloukas, Jordana Bell, Barbara E Engelhardt. Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements, Genome Biology, 16(1):14, 2015. [bibtex] [pdf] [doi]
Stephanie M van Den Berg, Marleen HM de Moor, Karin JH Verweij, Robert F Krueger, Michelle Luciano, Alejandro Arias Vasquez, Lindsay K Matteson, Jaime Derringer, Tõnu Esko, Najaf Amin, others. Meta-analysis of genome-wide association studies for extraversion: Findings from the Genetics of Personality Consortium, Behavior Genetics, Springer, 2015. [bibtex] [pdf] [doi]
David Mimno, David M Blei, Barbara E Engelhardt. Posterior predictive checks to quantify lack-of-fit in admixture models of latent population structure, Proceedings of the National Academy of Sciences, 112(26):E3341–50, 2015. [bibtex] [pdf] [doi]
Barbara E Engelhardt, Christopher D Brown. Diving deeper to predict noncoding sequence function, Nature Methods (News & Views; not peer-reviewed), Nature Publishing Group, 12(10):925–926, 2015. [bibtex] [pdf]
Amy B Hart, Eric R Gamazon, Barbara E Engelhardt, Pamela Sklar, Anna K Kähler, Christina M Hultman, Patrick F Sullivan, Benjamin M Neale, Stephen V Faraone, Harriet de Wit, Nancy J Cox, Abraham a Palmer. Genetic variation associated with euphorigenic effects of d-amphetamine is associated with diminished risk for schizophrenia and attention deficit hyperactivity disorder, Proceedings of the National Academy of Sciences of the United States of America, 111(16):5968–73, 2014. [bibtex] [pdf] [doi]
Lara M Mangravite*, Barbara E Engelhardt*, Marisa W Medina, Joshua D Smith, Christopher D Brown, Daniel I Chasman, Brigham H Mecham, Bryan Howie, Heejung Shim, Devesh Naidoo, QiPing Feng, Mark J Rieder, Yii-Der I Chen, Jerome I Rotter, Paul M Ridker, Jemma C Hopewell, Sarah Parish, Jane Armitage, Rory Collins, Russell A Wilke, Deborah A Nickerson, Matthew Stephens, Ronald M Krauss. A statin-dependent QTL for GATM expression is associated with statin-induced myopathy, Nature, 502(7471):377–80, 2013. [bibtex] [pdf] [doi]
Fantine Mordelet, John Horton, Alexander J Hartemink, Barbara E Engelhardt, Raluca Gordân. Stability selection for regression-based models of transcription factor-DNA binding specificity, Bioinformatics, 29(13):i117–25, 2013. [bibtex] [pdf] [doi]
Christopher D Brown, Lara M Mangravite, Barbara E Engelhardt. Integrative modeling of eQTLs and cis-regulatory elements suggests mechanisms underlying cell type specificity of eQTLs, PLoS Genetics, 9(8):e1003649, 2013. [bibtex] [pdf] [doi]
Kathryn E Muratore, Barbara E Engelhardt, John R Srouji, Michael I Jordan, Steven E Brenner, Jack F Kirsch. Molecular function prediction for a family exhibiting evolutionary tendencies toward substrate specificity swapping: Recurrence of tyrosine aminotransferase activity in the I$\alpha$ subfamily, Proteins: Structure, Function, and Bioinformatics, Wiley Online Library, 81(9):1593–1609, 2013. [bibtex] [pdf]
Amy B Hart*, Barbara E Engelhardt*, Margaret C Wardle, Greta Sokoloff, Matthew Stephens, Harriet de Wit, Abraham Palmer.Genome-wide association study of d-amphetamine response in healthy volunteers identifies putative associations, including cadherin 13 (CDH13), PLoS One, 7(8):e42646, 2012. [bibtex] [pdf] [doi]
Barbara E Engelhardt, Michael I Jordan, John R Srouji, Steven E Brenner. Genome-scale phylogenetic function annotation of large and diverse protein families, Genome Research, 21(11):1969–80, 2011. [bibtex] [pdf] [doi]
Barbara E Engelhardt, Matthew Stephens. Analysis of population structure: A unifying framework and novel methods based on sparse factor analysis, PLoS Genetics, 6(9):e1001117, 2010. [bibtex] [pdf] [doi]
Joseph K Pickrell, John C Marioni, Athma A Pai, Jacob F Degner, Barbara E Engelhardt, Everlyne Nkadori, Jean-Baptiste Veyrieras, Matthew Stephens, Yoav Gilad, Jonathan K Pritchard. Understanding mechanisms underlying human gene expression variation with RNA sequencing, Nature, 464(7289):768–772, 2010. [bibtex] [pdf] [doi]
Barbara E Engelhardt, Michael I Jordan, Steven E Brenner. A graphical model for predicting protein molecular function, Proceedings of the 23rd International Conference on Machine Learning (ICML), 2006. [bibtex] [pdf] [doi]
Barbara E Engelhardt, Michael I Jordan, Kathryn E Muratore, Steven E Brenner. Protein molecular function prediction by Bayesian phylogenomics, PLoS Computational Biology, 1(5):e45, 2005. [bibtex] [pdf] [doi]

* indicates equal authorship