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Pre-prints

  • Feinberg V, Cheng L-F, Li K, Engelhardt BE. ``Large linear multi-output Gaussian process learning for time series" (submitted) [arXiv]

  • McDowell IC, Manandhar D, Vockley CM, Schmid A, Reddy TE*, Engelhardt BE*. "Clustering gene expression time series data using an infinite Gaussian process mixture model" (submitted) [bioRxiv]

  • Jo B*, He Y*, Strober BJ*, Parsana P*, Aguet F, Brown AA, Castel SE, Gamazon ER, Gewirtz A, Gliner G, Han B, He AZ, Kang EY, McDowell IC, Li X, Mohammadi P, Peterson CB, Quon G, Saha A, Segre AV, Sul JH, Sullivan TJ, Ardlie KG, Brown CD, Conrad DF, Cox NJ, Dermitzakis ET, Eskin E, Kellis M, Lappalainen T, Sabatti C, GTEx Consortium, Engelhardt BE*, Battle A*. "Distant regulatory effects of genetic variation in multiple human tissues" (submitted) [bioRxiv]

  • Basbug ME, Engelhardt BE. "Coupled compound Poisson factorization" (submitted) [arXiv]

  • Aguiar D, Cheng L-F, Dumitrascu B, Mordelet F, Pai AA, Engelhardt BE. ``BIISQ: Bayesian nonparametric discovery of Isoforms and Individual Specific Quantification" (submitted) [arXiv]

  • Cheng L-F, Darnell G, Chivers C, Draugelis ME, Li K, Engelhardt BE. ``Sparse multi-output Gaussian processes for medical time series prediction" (submitted) [arXiv]

  • Sabnis G, Pati D, Engelhardt BE, Pillai N. "A divide and conquer strategy for high dimensional Bayesian factor models" (submitted) [arXiv]

  • Dumitrascu B, Darnell G, Ayroles J, Engelhardt BE. "A Bayesian test to identify variance effects" (submitted) [arXiv] [Software]

  • Valente A, Ginsburg G, Engelhardt BE. "Nonparametric reduced-rank regression for multi-SNP, multi-trait association mapping" (submitted) [arXiv] [Software]

  • McDowell IC, Pai AA, Guo C, Vockley CM, Brown CD, Reddy TE, Engelhardt BE. "Many long intergenic non-coding RNAs distally regulate mRNA gene expression levels" (in review) [BiorXiv]

  • Basbug ME, Engelhardt BE. "Clustering with beta divergences" (submitted) [arXiv]

  • Engelhardt BE, Adams RP. "Bayesian structured sparsity from Gaussian fields" (in review) [ArXiV] [Software]

  • Gao C, Brown CD, Engelhardt BE. "A latent factor model with a mixture of sparse and dense factors to model gene expression data with confounding effects" (in review) [ArXiV] [Software]

Publications

  • Dumitrascu B, Feng K, Engelhardt BE (2019). "PG-TS: Improved Thompson sampling for logistic contextual bandits" Neural Information Processing Systems (NeurIPS) [pdf]

  • GTEx Consortium, Battle A*, Brown CD*, Engelhardt BE*, Montgomery S* (2017). "Genetic effects on gene expression across human tissues" (Nature).

  • Saha A, Kim Y, Gewirtz ADH, Jo B, Gao C, McDowell IC, GTEx Consortium, Engelhardt BE*, Battle A*. "Co-expression networks reveal the tissue-specific regulation of transcription and splicing" (Genome Research). [bioRxiv]

  • Prasad N, Cheng L-F, Chivers C, Draugelis M, Engelhardt BE (2017). "A reinforcement learning approach to weaning of mechanical ventilation in intensive care units" Uncertainty in Artificial Intelligence (UAI). [arXiv].

  • Zhao S, Engelhardt BE, Mukherjee S, Dunson DB (2017). "Fast moment estimation for generalized latent Dirichlet models" Journal of the American Statistical Association (JASA). [pdf] [code]

  • Srivastava S, Engelhardt BE, Dunson DB (2017). "Expandable factor analysis" Biometrika. [pdf]

  • Darnell G, Georgiev S, Mukherjee S, Engelhardt BE (2017). "Adaptive randomized dimension reduction on massive data" (accepted, Journal of Machine Learning Research [JMLR]). [arXiv] [code]

  • Jerfel G, Basbug, ME, Engelhardt BE (2017). "Dynamic collaborative filtering with compound Poisson factorization" AISTATS. [pdf] [arXiv]

  • Cohen JD, Daw N, Engelhardt BE, Hasson U, Li K, Niv Y, Norman KA, Pillow J, Ramadge PJ, Turk-Browne NB, Willke TL (2017). "Computational approaches to fMRI analysis" Nature Neuroscience 20(3):304-313. [pdf]

  • Tonner PD, Darnell CD, Engelhardt BE*, Schmid A* (2016). "Detecting differential growth of microbial populations with Gaussian process regression" Genome Research 27(2):320-333. [pdf] [bioRXiv] [code]

  • Basbug ME, Engelhardt BE (2016). "Hierarchical compound Poisson factorization" Proceedings of the International Conference on Machine Learning (ICML) [pdf] [arXiv] [code]

  • Gao C, Zhao S, McDowell IC, Brown CD, Engelhardt BE (2016). "Context-specific differential gene co-expression networks via Bayesian biclustering models" PLOS Computational Biology 12(7):e1004791. [pdf] [code]

  • Zhao S, Gao C, Mukherjee S, Engelhardt BE (2016). "Bayesian group latent factor analysis with structured sparsity" Journal of Machine Learning Research 17(196):1-47. [pdf] [arXiv] [code]

  • Mimno D, Blei DM, Engelhardt BE (2015). "Posterior predictive checks to quantify lack-of-fit in admixture models of latent population structure," Proceedings of the National Academy of Sciences, 112(26):E3441-50. [pdf] [doi] [code]

  • Genetics of Personality Consortium (2015). "Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive Disorder," JAMA Psychiatry, 72(7):642-650. [pdf] [doi]

  • Zhang W, Spector T, Deloukas P, Bell JT*, Engelhardt BE* (2015). "Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements," Genome Biology, 16(1):14. [pdf]

  • Hart AB, Gamazon ER, Engelhardt BE, Sklar P, Kähler AK, Hultman CM, Sullivan PF, Neale BM, Faraone SV, Psychiatric Genomics Consortium: ADHD Subgroup, de Wit H, Cox NJ, Palmer A (2014). "Genetic variation associated with euphorigenic effects of d-amphetamine is associated with diminished risk for schizophrenia and ADHD" Proceedings of the National Academy of Sciences, 111(16): 5968--5973. [pdf]

  • Mangravite LM*, Engelhardt BE*, Medina MW, Mecham BH, Howie B, Shim H, Naidoo D, Smith JD, Rieder MJ, Nickerson DA, Stephens M*, Krauss RM* (2013). "A statin-dependent QTL for GATM expression is associated with statin-induced myopathy" Nature, 502: 377--380. [pdf] [Abstract] [The Scientist article]

  • Brown CD, Mangravite LM, Engelhardt BE (2013). "Integrative modeling of eQTLs and cis-regulatory elements suggests mechanisms underlying cell type specificity of eQTLs" PLoS Genetics, 9(8): e1003649. [pdf][arXiv][ASHG 2012 talk]

  • Mordelet F, Horton J, Hartemink A, Engelhardt BE, Gordan R (2013). "Stability selection for regression-based models of transcription factor-DNA binding specificity" Bioinformatics, 29(13):i117-i125. [link]

  • Muratore KE, Engelhardt BE, Srouji JR, Jordan MI, Brenner SE, Kirsch JF (2013). "Molecular function prediction for a family exhibiting evolutionary tendencies towards substrate specificity swapping: Recurrence of tyrosine aminotransferase activity in the Iα subfamily" Proteins, 81(9):1593-609. [Abstract]

  • Hart AB*, Engelhardt BE*, Wardel MC, Sokoloff G, Stephens M, de Wit H, Palmer AA (2012). "Genome-wide association study of d-amphetamine response in healthy human volunteers identifies putative associations, including cadherin 13 (CDH13)." PLoS ONE, 7(8):e42646. [pdf] [link]

  • Engelhardt BE, Jordan MI, Srouji JR, Brenner SE (2011) "Genome-scale phylogenetic function annotation of large and diverse protein families." Genome Research, 21(11) 1969-1980. [pdf] [SIFTER code] [supplemental]

  • Engelhardt BE, Stephens M (2010) "Analysis of population structure: a unifying framework and novel methods based on sparse factor analysis." PLoS Genetics, 6(9):e1001117. [pdf] [SFA code]

  • Pickrell JK, Marioni JC, Pai AA, Degner JF, Engelhardt BE, Nkadori E, Veyrieras JB, Stephens M, Gilad Y, Pritchard JK (2010) "Understanding mechanisms underlying human gene expression variation with RNA sequencing." Nature, 464:768-772. [link] [Nature Reviews Genetics article summary]

  • Engelhardt BE (2007) "Predicting protein molecular function." PhD Thesis, EECS Department, University of California, Berkeley. [pdf]

  • Engelhardt BE, Jordan MI, Brenner SE (2006) "A graphical model for predicting protein molecular function." Proceedings of the International Conference on Machine Learning (ICML). [pdf]

  • Engelhardt BE, Jordan MI, Muratore KE, Brenner SE (2005) "Protein molecular function prediction by Bayesian phylogenomics." PLoS Computational Biology, 1(40):646--649. [pdf]

  • Amir E, Engelhardt BE (2003) "Factored planning." Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). [pdf]

    • * indicates equal contribution to the manuscript.