bold: Lab members and advisees. *: Equal contribution. #: Correponding author.

Bayes Theory and Method

  1. Xie F, and Xu Y#,Carey Priebe and Joshua Cape
    Bayesian Estimation of Sparse Spiked Covariance Matrices in High Dimensions. Submitted.
  2. Xie F, and Xu Y#.
    Bayesian Projected Calibration of Computer Models. Submitted.
  3. Xu Y#, Thall P, Hua W, and Andersson B.
    Bayesian Nonparametric Survival Regression for Optimizing Precision Dosing of Intravenous Busulfan in Allogeneic Stem Cell Transplantation. Revision Submitted.
  4. Xie F, Jin W, and Xu Y#.
    A Theoretical Framework for Bayesian Nonparametric Regression: Orthonormal Random Series and Rates of Contraction. Submitted.
  5. Xie F, and Xu Y#.
    NDPP-Mix: Nested Dirichlet Process-Determinantal Point Process Mixture Model. Submitted
  6. Wang L, Xie F, and Xu Y#.
    Mixed Simultaneous Perturbation Stochastic Optimization for Order Selection and Parameter Estimation. Submitted.
  7. Gu M and Xu Y.
    Nonseparable Gaussian Stochastic Process: A Unified View and Computational Strategy. Submitted.
  8. Xie F, and Xu Y#.
    Bayesian Repulsive Gaussian Mixture Model. Manuscript
  9. Journal of the American Statistical Association (Theory and Methods). In Press.
  10. Xie F and Xu Y#.
    Adaptive Bayesian Nonparametric Regression using Kernel Mixture of Polynomials with Application to Partial Linear Model. Bayesian Analysis, Revision Submitted. Manuscript
  11. Müller P, Xu Y, and Jara A.
    Bayesian Nonparametrics.
  12. Journal of Statistical Research. 2017, 48-50.
  13. Thall P, Müller P, Xu Y, and Guindani M, Bayesian Nonparametric Statistics: A New Toolkit for Discovery in Cancer Research.
  14. Pharmaceutical Statistics. 2017, 16(6), 414-423.
  15. Xu Y, Müller P, and Telesca D, Bayesian Inference for Latent Biologic Structure with Determinantal Point Processes (DPP). Data and Code
  16. Biometrics. 2016, 72(3), 955-964
  17. Xu Y, Müller P, Wahed A and Thall P.
    Bayesian Nonparametric Estimation for Dynamic Treatment Regimes with Sequential Transition Times (with discussion). Manuscript Software Supplement
  18. Journal of the American Statistical Association. 2016, 111(515), 921-950
    (Winner of the 2015 David P. Byar Young Investigator Travel Award Sponsored by ASA Biometrics Section)
  19. Mitra R, Müller P, Liang S, Xu Y and Ji Y
    Towards the Discovery of the Histone Code - A Bayesian Graphical Model for Histone Modifications.
    Circulation: Cardiovascular Genetics, 2013; 6: 419-426.
  20. Xu Y, Lee J, Yuan Y, Mitra R, Liang S, Müller P and Ji Y.
    Nonparametric Bayesian Bi-Clustering for ChIP-Seq Count Data.
    Bayesian Analysis, 2013, 8(2): 1-22.
  21. Xu Y, Zhang J, Yuan Y, Mitra R, Müller P and Ji Y
    A Bayesian Graphical Model for Integrative Analysis of TCGA Data.
    IEEE Workshop on Genomic Signal Processing and Statisticss.2012: 135-138.
  22. Trindade A.A. and Xu Y.
    Quantile Versions of Holt-Winters Forecasting Algorithms.
    Journal of Statistics: Advances in Theory and Applications, 2011, 5(1): 15-35.

Electronic Health Record Data

  1. Xu Y, Xu Y, and Saria S.
    Bayesian Estimation of Individualized Treatment-Response Curves in Populations with Heterogeneous Treatment Effects.
  2. Journal of Machine Learning Research (Minor Revision)
  3. Xu Y, Xu Y, and Saria S.
    A Non-parametric Bayesian Approach for Estimating Treatment-Response Curves from Sparse Time Series.
  4. Proceedings of the 1st Machine Learning for Healthcare Conference. 2016, 282-300.

Computational Biology and Cancer Genomics

  1. Yuan Y, Ju Y, Kim Y, Li J, Weinstein J,, Xu Y, and
    Comprehensive Molecular Characterization of Mitochondrial Genomes in Human Cancers.
  2. Nature Genetics. In press.
  3. Genevieve L. Stein-O'Brien, Raman Arora, Aedin C. Culhane, Alexander V. Favorov, Casey S. Greene, Loyal A. Goff, Yifeng Li, Aloune Ngom, Michael F. Ochs, Xu Y, and Elana J. Fertig.
    Enter the matrix: Interpreting unsupervised feature learning with matrix decomposition to discover hidden knowledge in high-throughput omics data.
  4. Trends in Genetics. 2018 Oct;34(10):790-805.
  5. Li Y, Dinalankara W, Marchionni L, Kochel C, Nirschl T, Drake C, and Xu Y#.
    BayRepulsive: A Bayesian Repulsive Deconvolution Model for Inferring Tumor Heterogeneity (Submitted)
  6. Wei L, Jin Z, Yang S, Xu Y, Zhu Y, and Ji Y.
    TCGA-Assembler 2.0: Software Pipeline for Automatic Retrieval, Processing, and Integration of TCGA/CPTAC Data.
  7. Bioinformatics. 2018, 34(9):1615-1617.
  8. Xiao F, Niu Y, Hao N, Jin Z, Xu Y, and Zhang H, modSaRa: a computationally efficient R package for CNV identification.
  9. Bioinformatics. 2017, 33(15): 2384-2385.
  10. Xie F, Zhou M, and Xu Y.
    BayCount: A Bayesian Decomposition Method for Inferring Tumor Heterogeneity using RNA-Seq Counts.
  11. Annals of Applied Statistics. 2018, 12(3): 1605-1627.
  12. Yuan Y, Liu L, Chen H, Wang Y, Xu Y, Mao H, Li J, Mills GB, Shu Y, Li L, Liang H.
    Comprehensive characterization of molecular differences in cancer between male and female patients.
  13. Cancel Cell. 2016, 29(5): 711-722
  14. Zhu Y*, Xu Y*, Helseth D*, Gulukota K, Yang S, Pesce L, Mitra R, Müller P, Sengupta S, Guo W, Silverstein J, Foster I, Parsad N, White K and Ji Y.
    Zodiac: A Comprehensive Depiction of Genetic Interactions in Cancer by Integrating TCGA Data. Manuscript Software
  15. Journal of the National Cancer Institute. 2015, 107(8): djv129.
  16. Xu Y, Müller P, Yuan Y, Gulukota K and Ji Y.
    MAD Bayes for Tumor Heterogeneity Feature Allocation with Exponential Family Sampling. Manuscript Software
  17. Journal of the American Statistical Association. 2015, 110(510): 503-514.
  18. Yuan Y, Van Allen EM, Omberg L, Wagle N, Sokolov A, Xu Y, and et al.
    Assessing the Clinical Utility of Cancer Genomic and Proteomic Data across Tumor Types.
    Nature Biotechnology. 2014, 32: 644-652
  19. Han L, Yuan Y, Zheng S, Yang Y, Li J, Edgerton M, Diao L, Xu Y, Verhaak R and Liang H.
    The Pan-Cancer Analysis of Pseudogene Expression Reveals Biologically and Clinically Relevant Tumor Subtypes.
    Nature Communications. 2014, 5: 3963
  20. Costello JC, Heiser LM, Georgii E, Gönen M, Menden MP, Wang NJ, Bansal M, Ammad-ud-din M, Hintsanen P, Khan SA, Mpindi JP, NCI DREAM Community (including Xu Y), Kallioniemi O, Honkela A, Aittokallio T, Wennerberg K, Collins JJ, Gallahan CD, Singer D, Saez-Rodriguez J, Kaski S, Gray JW, Stolovitzky G.
    A community effort to assess and improve drug sensitivity prediction algorithms.
    Nature Biotechnology. 2014, 32(12):1202-1212.
  21. Xu Y, Zheng X, Yuan Y, Estecio M, Issa J-P, Ji Y and Liang S.
    BM-SNP: A Bayesian Model for SNP Calling using High Throughput Sequencing Data. Supplement
    IEEE/ACM transactions on computational biology and bioinformatics. 2014, 11(6):1038-44.
  22. Ji Y, Xu Y, Zhang Q, Tsui K-W, Yuan Y, Liang S and Liang H
    BM-Map: Bayesian Mapping of Multireads for Next-Generation Sequencing Data.
    Biometrics, 2011 Dec; 67(4): 1215-24.
  23. (Winner of the 2011 ENAR Distinguished Student Paper Award)
  24. Xu Y, Zheng X, Yuan Y, Estecio M, Issa J-P, Ji Y and Liang S
    A Bayesian Model for SNP Discovery Based on Next-Generation Sequencing Data.
    IEEE Workshop on Genomic Signal Processing and Statisticss. 2012: 42-45.
  25. Yuan Y, Xu Y, Xu J and Liang H
    Predicting the lethal phenotype of the knockout mouse by integrating genomic data.
    Bioinformatics, 2012 May 1; 28(9): 1246-52.
  26. Yuan Y, Norris C, Xu Y, Tsui KW, Ji Y and Liang H
    BM-Map: an efficient software package for accurately allocating multireads of RNA-seq data.
    BMC Genomics, 2012, 13(Suppl 8): S9.

Bayesian Clincal Trial Design

  1. Xu Y, Constantine F, Yuan Y and Pritchett Y, ASIED: A Bayesian Adaptive Subgroup-Identification Enrichment Design. Submitted. Manuscript
  2. Xu Y, Müller P, and Thall P, Bayesian Subgroup-Based Adaptive Designs in Sequential, Multiple Assignment, Randomized Biomarker Trials (SMART). In preparation.
  3. Xu Y and Ji Y.
    A Latent Gaussian Process Model with Application to Monitoring Clinical Trials. In preparation. Manuscript Software
  4. Müller P, Xu Y, and Thall P. Clinical Trial Design as a Decision Problem.
  5. Applied Stochastic Models in Business and Industry. DOI: 10.1002/asmb.2222.
  6. Xu Y, Müller P, Tsimberidou A, and Berry D.
    A Nonparametric Bayesian Basket Trial Design.
    Biometrical Journal. Accepted. Manuscript
  7. Xie F, and Xu Y#, Bayesian Repulsive Gaussian Mixture Model. Manuscript
  8. Xu Y, Thall P, Müller P, and Mehran R, A Decision-Theoretic Comparison of Treatments to Resolve Air Leaks After Lung Surgery Based on Nonparametric Modeling. Supplement
  9. Bayesian Analysis. 2017, 12(3), 639-652.
  10. Xu Y, Trippa L, Müller P and Ji Y.
    Subgroup-Based Adaptive (SUBA) Designs for Multi-Arm Biomarker Trial. Manuscript
  11. Statistics in Biosciences. 2014, DOI: 10.1007/s12561-014-9117-1
    (1st Place Winner of the 2014 JSM Biopharmaceutical Section Student Paper)

Book Chapter

  1. Faraji F, Schubert A, Kagohara L, Tan M, Xu Y, Zaidi M, Fortin JP, Fakhry C, Izumchenko E, Gaykalova D, and Fertig E. Genome-wide molecular landscapes of HPV-positive and HPV-negative head and neck squamous cell carcinoma.
  2. Xu Y, Zhu Y and Ji Y, Graphical models for integrating omics data. In: Integrating omics data: statistical and computational methods. Editors: George C. Tseng, Xianghong Jasmine Zhou and Debashis Ghosh. This book is under copyediting and production in Cambridge University Press; expected in early 2015.
  3. Xu Y, Ji Y and Müller P, Biomarker-Driven Adaptive Design. In: Nonparametric Bayesian Methods in Biostatistics and Bioinformatics. Editors: Mitra R and Müller P. Springer-Verlag, to appear.