Publications in Peer-review Journals, Proceedings, and Abstracts:


  1. Ni, Y., Mueller, P., and Ji, Y. "Heterogeneous Reciprocal Graphical Models." Invited for revision in Biometrics
  2. Ni, Y., Ji, Y., and Mueller, P. "Reciprocal Graphical Models for Integrative Gene Regulatory Network Analysis." Submitted.
  3. Zhou, T., Mueller, P., Sengupta, S. and Ji, Y. PairClone: A Bayesian Subclone Caller Based on Mutation Pairs.
  4. Zhou, T., Sengupta, S., Mueller, P., Ji, Y. PairCloneTree: Reconstruction of Tumor Subclone Phylogeny Based on Mutation Pairs using NGS Data.
  5. Zuanetti, DA., Mueller, P, Zhu, Y., Yang, S., Ji, Y. Clustering Distributions with the Marginalized Nested Dirichlet Process
  6. Zuanetti, DA., Mueller, P., Zhu, Y., Yang, S., Ji, Y. Bayesian nonparametric clustering for large data sets
  7. Lee, J., Sengupta, S., Hovey, R., Ji, Y. Bayesian Nonparametric Inference for Tumor Purity and Tumor Subclones
  8. Rosner, G., Bekele, BN, Ji, Y. Bayesian Designs in Clinical Trials. (Book Chapter)
  9. Guo, W., Wang, SJ., Yang, S, Lynn, H., Ji, Y. A Bayesian Interval Dose-Finding Design Addressing Ockham’s Razor: mTPI-2
  10. Pectacides, E., et. al., Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma. New England Journal of Medicine. Submitted.


  1. Maron, S. B., Luke, J. J., Hovey, R., Bao, R., Gajewski, T., Ji, Y., Catenacci, D. Identification of T cell-inflamed gastric adenocarcinoma in TCGA. ASCO-SITC Clinical Immuno-Oncology Symposium 2017. In press. 2017


  1. Lee, J, Thall, P, Ji, Y and Mueller, P.   A Decision-Theoretic Phase I-II Design for Ordinal Outcomes in Two Cycles. Biostatistics 2016. 17(2):304-319.
  2. Guo, W, Ji, Y* and Catenacci, D.   A Subgroup Cluster Based Bayesian Adaptive Design for Precision Medicine. Biometrics In press
  3. Lee, J, Mueller, P, Sengupta, S, Gulukota, K, and Ji Y*.  Bayesian inference for intratumour heterogeneity in mutations and copy number variation. Journal of the Royal Statistical Society: Series C. Applied Statistics. 2016. 65(4):547-563.
  4. Mitra R, Mueler P, Ji Y.  Bayesian Multiplicity Control for Graphs. In press, Canadian Journal of Statistics In press.
  5. Mitra, R., Mueller, P., Ji, Y. Bayesian graphical models for differential pathways. Bayesian Analysis. 2016. 11(1):99-124.
  6. Sengupta, S, Zhou, T, Mueller, P, and Ji Y* .   A Bayesian Nonparametric Model for Reconstructing Tumor Subclones Based on Mutation Pairs. PSB 2016 Vol. 21, p.393
  7. Mitra R, Mueller P, Ji Y . Bayesian graphical models for differential pathways. Bayesian Analysis 2016. 11(1):99-124
  8. Burnside, ES, Drukker, K, Hui, L, et al. ML Using computer-extracted image phenotypes from tumors on breast magnetic resonance imaging to predict breast cancer pathologic stage. Cancer 2016. 122(5):748-757.
  9. H. Li, Y. Zhu, E. Burnside, E. Huang, K. Drukker, K. Hoadley, C. Fan, S. Conzen, M. Zuley, J. Net, E. Sutton, G. Whitman, E. Morris, C. Perou, Y. Ji* , and M. Giger*.   Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA Dataset, NPJ Breast Cancer , 2, Article number: 16012, 2016.
  10. Li, H., Y. Zhu, E.S. Burnside, K. Drukker, K.A. Hoadley, C. Fan, S.D. Conzen, L. Lan, M. Zuley, G. Whitman, E.J. Sutton, J.M. Net, M. Ganott, K.R. Brandt, E. Bonaccio, A. Rao, C. Jaffe, E Huang, J.B. Freymann, J. Kirby, E. Morris, C.M. Perou, Y. Ji,* M.L. Giger*. MRI radiomics signatures for predicting the risk of breast cancer recurrence as given by research versions of gene assays of MammaPrint, Oncotype DX, and PAM50. Radiology, 2016 May 5:152110
  11. Li, D.H., Whitmore, J.B., Guo, W., Ji, Y*. Toxicity and Efficacy Probability Interval Design for Phase 1 Adoptive Cell Therapy Dose-Finding Clinical Trials. Clinical Cancer Research. 2016. DOI: 10.1158/1078-0432.CCR-16-1125
  12. Narayanan, J., Dobrin, S., Choi, J., Rubin, S., Pham, A., Patel, V., Frigerio, R., Maurer, D., Gupta, P., Link, L., Walters, S., Wang, C., Ji, Y., Maraganore, D. Structured clinical documentation to improve quality and support practice based research in epilepsy. Epilepsia. 58 (1), 68-76. 2016


  1. Yang, S, Wang, SJ, Ji, Y*   Integrated Dose-Finding Tool for Phase I Trials in Oncology. Contemporary Clinical Trials. 2015. 45:426-434.
  2. Guo, W., Li, H., Zhu, Y., Lan, L., Yang, S., Drukker, K., Giger, M.L., Ji, Y* .   Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data. Journal of Medical Imaging. 2015. 2(4):041007.
  3. Sengupta, S, Gulukota, K, Zhu, Y and Ji Y*. Local-Haplotype Variant Calling Reveals Cellular Heterogeneity and Somatic Mosaicism. NAR. 2015. 44(3):e25.
  4. Guo W, Ni Y, Ji Y* TEAMS: Toxicity- and Efficacy-based Dose Insertion Design with Adaptive Model Selection for Phase I/II Dose-Escalation Trials in Oncology. Statistics in Biosciences . 2015. 7(2):432-459.
  5. Zhu Y, Xu Y, Helseth L, ... Ji Y*.   Zodiac: A Comprehensive Depiction of Genetic Interactions in Cancer by Integrating TCGA Data. JNCI 2015 May 8;107(8). pii: djv129.
  6. Sengupta S, Gulukota K, Lee J, Mueller, P, Ji Y*.   BayClone: Bayesian Nonparametric Inference of Tumor Subclones Using NGS Data. Pacific Symposium of Biocomputing 2015:467-478.
  7. Xu Y, Mueller P*, Yuan Y, Gulukota K, Ji Y* . MAD Bayes for Tumor Heterogeneity -- Feature Allocation with Exponential Family Sampling. Journal of American Statistical Association 2015. 110(510):503-514
  8. Lee J, Mueler P*, Ji Y, Gulukota K. A Bayesian Feature Allocation Model for Tumor Heterogeneity. AOAS 2015. 9(2):621-639
  9. Nieto L, Ji Y , Baladandayuthapany V.   A semiparametric Bayesian model for comparing DNA copy numbers. Brazilian Journal of Probability and Statistics
  10. Lee, JH, Thall, PF, Ji Y, Mueller, P. Bayesian Dose-Finding in Two Treatment Cycles Based on the Joint Utility of Efficacy and Toxicity. Journal of American Statistical Association. 2015. 110(510):711-722
  11. Lee, JH, Ji Y, Liang, S, Cai, G, Mueller, P. Bayesian Hierarchical Model for Differential Gene Expression Using RNA-Seq Data. Statistics in Biosciences. 2015. 7(1):48-67.
  12. Zhu, Y., Li, H., Guo, W., Drukker, K., Lan, L, Giger, M*, Ji, Y*. Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma. Scientific Reports. 5, 2015.
  13. Yajima, M., Telesca, D., Ji, Y., Mueller, P. Detecting differential patterns of interaction in molecular pathways. Biostatistics. 16(2):240-251, 2015.


  1. Guha S, Ji Y , Baladandayuthapani V. Bayesian Disease Classification using Copy Number Data Cancer Informatics In press.
  2. Mitra R, Mueller P, Qiu P, Ji Y* Bayesian Hierarchical Models for Protein Networks in Single Cell Mass Cytometry Cancer Informatics In press.
  3. Xu Y, Trippa L, Mueller P, Ji Y*. Subgroup-Based Adaptive (SUBA) Designs for Multi-Arm Biomarker Trials. Statistics in Biosciences In press.
  4. Mueller P, Mitra R, and Ji Y. Bayesian Graphical Models for Epigenomic Heterogeneity. In the proceedings volume of the 8th Triennial Calcutta Symposium In press.
  5. Mitra R, Muller P*, Ji Y* Zhu Y, Mills G, Lu Y. A Bayesian Hierarchical Model for Inference Across Related  RPPA Experiments. Journal of Applied Statistics In press
  6. Pan H, Xie F, Liu P, Xia J*, Ji Y*. A Phase I/II Seamless Dose Escalation/Expansion with Adaptive Randomization Scheme (SEARS). Clinical Trials. 2014; 11(1):49-59. 
  7. Zhu Y, Qiu P, Ji Y*.   TCGA-Assembler: Open-Source Software for Assembling, and Processing TCGA Data. Nature Methods   11(6):599-600.
  8. Baladandayuthapani V, Talluri R, Ji Y, Coombes KR, Hennessey BT, Davies M, Mallick BK.   Bayesian sparse graphical models for classification with application to protein expression data. Annals of Applied Statistics  In press.
  9. Cai C, Ji Y, Ying Y. A Bayesian Dose-finding Design for Oncology Clinical Trials of Combinational Biological Agents.   Journal of Royal Statistical Society, Series C (Applied Statistics). 2014;63(1):159-173.
  10. Zhu Y, Ji Y , Bhayani M. A Computational Approach to the Identification of Prognostic Biomarkers in Head and Neck Squamous Cell Carcinoma. Abstract accepted for IFHNOS 5th World Congress/AHNS 2014 Annual Meeting
  11. Burnside, ES, Giger, M, ... Ji, Y. Using Computer-extracted Features from Tumors on Breast MRI to Predict Stage. Abstract accepted for RSNA 2015 Annual Meeting
  12. Giger, ML, Li H, ... Ji, Y, et al. Relationship of quantitative MRI-based phenotypes and the molecular classifications of breast cancers in the TCGA/TCIA dataset. Abstract accepted for RSNA 2015 Annual Meeting


  1. Xu Y, Zheng X, Yuan Y, Marcos RS, Issa JP, Qiu, P, Ji Y*, Liang S*. BM-SNP: A Bayesian Model for SNP Calling using High-Throughput Sequencing Data. BMC Genomics Suppl. In press.
  2. Lee J, Ji Y*, Shoudan L, Cai G, Mueller P*. Bayesian Hierarchical Model for Differential Gene Expression Using RNA-Seq Data. Statistics in Biosciences. In press.
  3. Mitra R, Mueller P, Liang S, Xu Y, Ji Y*. Towards Breaking the Histone Code – Bayesian Graphical Models for Histone Modifications. Circulation: Cardiovascular Genetics. 2013;6(4):419-26.
  4. Liu Y, Ji Y, Qiu P*. Identification of thresholds for dichotomizing DNA methylation data. EURASIP Journal on Bioinformatics and Systems Biology. 2013;2013(1):8.
  5. Trentini F, Ji Y*, Mueller P, Qi Y, Iwamoto T, Pusztai L. Bayesian Mixture Models for Assessment of Gene Differential Behaviour and Prediction of pCR through the integration of copy number and gene expression data. PLoS ONE. 8(7): e68071. 
  6. Ji Y*, Wang S-J. The mTPI Design: A Safer and More Reliable Method than the 3+3 Design for Practical Phase I Trials. Journal of Clinical Oncology. 31(14):1785-91, 2013.
  7. Mitra, R., Mueller, P.*, Ji, Y.*. Propriety conditions for the Bayesian autologistic model – Inference for Histone Modifications. Journal of Statistical Theory and Practice. 7(2):248-258, 2013.
  8. Mitra R, Mueller, P*, Liang, S, Yue, L, Ji Y*. A Bayesian Graphical Model for ChIP- Seq Data on Histone Modifications. Journal of American Statistical Association 108: 69-80, 03/2013.
  9. Ji Y, Wang S-J. Safety Concerns of the 3+3 Design: A Comparison to the mTPI Design. In the 2012 ICSA Applied Statistics Symposium Proceedings. 2013.
  10. Hu B, Ji Y*, Xu Y, Ting AH*. Screening for SNPs with Allele-Specific Methylation based on Next-Generation Sequencing Data. Statistics in Biosciences. 5(1):179-197, 2013.
  11. Xu Y, Lee J, Yuan Y, Mitra R, Liang S, Mueller P, Ji Y*. Nonparametric Bayesian Bi-Clustering for ChIP-Seq Count Data. Bayesian Analysis. 8(2):1-22, 2013.
  12. Marsh R, Talamonti M, Ji Y. Editorial -- Effects of adjuvant chemotherapy with Fluorouracil plus Folinic Acid or Gemcitabine vs observation on survival in patients with resected periampullary adenocarcinoma. Transl Gastrointest Cancer 2013 Feb 20. doi: 10.3978/j.issn.2224-4778.2013.02.03.
  13. Pan H, Ji Y, Chen Z, Li C, Xia J*. The choice of phase I Bayesian adaptive designs in China. International Journal of Drug Discovery. 5(1):185-190. 2013.
  14. Lee J, Mueller P, Ji Y*. A nonparametric Bayesian model for local clustering. Journal of the American Statistical Association. 2013;108(503).
  15. Ji Y, Pan H.A Comparison of Three Adaptive Designs for Phase I Clinical Trials. In Important considerations for clinical trial methodologies (edited by Williamson R). 2013.
  16. Mitra R, Mueller P, Ji Y*. Bayesian model-based approaches for solexa sequencing data. In Advances in Statistical Bioinformatics (editted by Do KA, Qin ZS, Vannucci M). 2013.
  17. Ji Y, Trentini F, Mueller P. A Bayesian framework for integrating copy number and gene expression data. In Advances in Statistical Bioinformatics (editted by Do KA, Qin ZS, Vannucci M). 2013.


  1. Lemoine M, Derenzini E, Buglio D, Medeiros LJ, Davis RE, Zhang J, Ji Y, Younes A. The pan-deacetylase inhibitor panobinostat induces cell death and synergizes with everolimus in Hodgkin lymphoma cell lines. Blood. 119(17):4017-25, 04/2012.
  2. Xie F, Ji Y, Tremmel LT. A Bayesian adaptive design for multi-dose, randomized, placebo-controlled phase I/II trials. Contemporary Clinical Trials. 33(4):739-48, 07/2012.
  3. Yuan Y, Norris C, Xu Y, Tsui KW, Ji Y*, Liang H *. BM-Map: an efficient software package for accurately allocating multireads of RNA-seq data. BMC Genomics. 13 Suppl 8:S9. Epub 12/2012.
  4. Telesca D*, Mu ̈ller P, Kornblau S, Suchard MA, Ji Y*. Modeling Protein Expres- sion and Protein Signaling Pathways. Journal of American Statistical Association, 107:500, 1372-1384, 12/2012.
  5. Xu Y*, Zhang J, Yuan Y, Mitra R, Mu ̈ller P, Ji Y*. A Bayesian Graphical Model for Integrative Analysis of TCGA Data. In 2012 IEEE International Workshop on Genomic Signal Processing and Statistics.
  6. Mitra R, Mu ̈ller P*, Ji Y*, Mills G, Lu Y. Sparse Bayesian Graphical Models for RPPA Time Course Data. In 2012 IEEE International Workshop on Genomic Signal Processing and Statistics.
  7. Xu Y, Zheng X, Yuan Y, Estecio M, Issa J-P, Ji Y*, Liang S*. A Bayesian Model for SNP Discovery Based on Next-Generation Sequencing Data. In 2012 IEEE International Workshop on Genomic Signal Processing and Statistics.
  8. Li H, Gallegos J, Su X, Lu Y, Molldrem JJ, Ji Y, Liang S*. dsPIG: a Tool to Predict Imprinted Genes from the Deep Sequencing of Whole Transcriptomes. BMC Bioinformatics. 13:271. 10/2012.
  9. Ji Y, Feng L, Shpall EJ, Kebriaei P, Champlin R, Berry D, Cooper LJN. Bayesian Continual Reassessment Method for Dose-Finding Trials Infusing T Cells with Lim- ited Sample Size. Journal of Biopharmaceutical Statistics. 22(6):1206-19, 2012.
  10. Ji Y, Mitra R, Quintana F, Jara A, Mu ̈ller P, Liu P, Lu Y, Liang S,. BABC – Bayesian base calling for Solexa sequence data. BMC Bioinformatics. 13 Suppl 13:S6, 2012.
  11. Cai G, Li H, Lu Y, Lee JH, Mu ̈ller P, Ji Y, Liang S,. Accuracy of RNA-Seq and its dependence on sequencing depth. BMC Bioinformatics. 13 Suppl 13:S5, 2012.
  12. Nieto-Barajas L, Mu ̈ller P, Ji Y, Lu Y, Mills, G. A Time-Series DDP for Functional Proteomics Profiles. Biometrics. 68(3):859-68, 09/2012.


  1. Ji Y*, Xu, Y, Zhang, Q, Tsui, K-W, Yuan, Y, Liang, S, Liang, H*. BM-Map: Bayesian Mapping of Multireads for Next-Generation Sequencing Data. Biometrics. 67(4):1215-24, 12/2011.
  2. FanaleM,FayadL,ProB,SamaniegoF,LiboonMJ,NunezC,HorowitzS,Anderlini P, Popat U, Ji Y, Kwak LW, Younes A. Phase I Study of Bortezomib Plus ICE (BICE) for the Treatment of Relapsed/Refractory Hodgkin Lymphoma. British Journal of Hematology. 154(2):284-6, 07/2011.
  3. Lee JH, Mu ̈ller P*, Liang S, Cai G, Ji Y*. On Differential Gene Expression Using RNA-Seq Data. Cancer Informatics. 10:205-15, 2011.
  4. Younes A, Oki Y, Bociek GR, Kuruvilla J, Fanale M, Neelapu S, Copeland A, Buglio D, Galal A, Besterman J, Li Z, Drouin M, Patterson T, Ward MR, Paulus JK, Ji Y, Medeiros LJ, and Martell, RE. Phase II Study of Mocetinostat (MGCD0103) In Patients with Relapsed and Refractory Classical Hodgkin Lymphoma. Lancet Oncology. 12(13):1222-8, 12/2011.
  5. Derenzini E, Lemoine M, Buglio D, Katayama H, Ji Y, Davis E, Sen S, Younes A. The JAK inhibitor AZD1480 regulates proliferation and immunity in Hodgkin lymphoma. Blood Cancer. 1(12):e46, 12/2011.
  6. Jona A, Khaskhely N, Buglio D, Shafer JA, Derenzini E, Bollard C, Medeiros LJ, Illes A, Ji Y, Younes A. The histone deacetylase inhibitor entinostat (SNDX-275) induces apoptosis in Hodgkin lymphoma cells and synergizes with Bcl-2 family in- hibitors. Exp Hematol, 39(10): 1007-1017, 10/2011.
  7. Buglio D, Palakurthi S, Vega-Vasquez F, Neelapu S, Berry D, Ji Y, Byth K, Younes A. Inhibition of Tak-1 by AX-Tak1 Imparis NF-κB Activation, Down regulates XIAP and Activates Caspase-9 Inducing Apoptotis in Mantle Cell Lymphoma. ASH 2011, 12/2011.


  1. Hu B, Bekele BN, Ji Y*. Adaptive Dose Insertion in Early Phase Clinical Trials. Clinical Trials. e-Pub 9/2010.
  2. Ji Y, Liu P, Li Y, Bekele BN. A modified toxicity probability interval method for dose-finding trials. Clinical Trials. 7(6):653-63, 12/2010.
  3. Zhou X, Teegala S, Huen A, Ji Y, Fayad L, Hagemeister FB, Gladish G, Vadhan- Raj S. Incidence and Risk Factors of Venous Thromboembolic Events in Lymphoma. Am J Med 123:935-41, 10/2010.
  4. Baladandayuthapani V, Ji Y, Morris J, Talluri R, Nieto-Barajas L. Bayesian Ran- dom Segmentation Models to Identify Shared Copy Number Aberrations for Array CGH Data. Journal of American Statistical Association 105:1358-1375, 12/2010.
  5. Bekele BN, Li Y, Ji Y. Risk-group-specific dose finding based on an average toxicity score. Biometrics 66:541-8, 6/2010.


  1. Berkova Z, Wang S, Wise JF, Maeng H, Ji Y, Samaniego F. Mechanism of Fas signaling regulation by human herpesvirus 8 K1 oncoprotein. J Natl Cancer Inst 101:399-411, 3/2009.
  2. Ji Y, Bekele BN. Adaptive randomization for multi-arm comparative clinical trials based on joint efficacy/toxicity outcomes. Biometrics 65:876-84, 9/2009.
  3. Wang M, Oki Y, Pro B, Romaguera JE, Rodriguez MA, Samaniego F, McLaughlin P, Hagemeister F, Neelapu S, Copeland A, Samuels BI, Loyer EM, Ji Y, Younes A. Phase II Study of Yttrium-90-Ibritumomab Tiuxetan in Patients With Relapsed or Refractory Mantle Cell Lymphoma. J Clin Oncol 27:5213-8, 11/2009.


  1. Bekele BN, Ji Y, Shen Y, Thall PF. Monitoring late-onset toxicities in phase I trials using predicted risks. Biostatistics 9:442-57, 7/2008.
  2. Sun M, Estrov Z, Ji Y, Coombes KR, Harris DH, Kurzrock R. Curcumin (Difer- uloylmethane) Alters the Expression Profiles of MicroRNAs in Human Pancreatic Cancer Cells. Mol Cancer Ther 7:464-473, 3/2008.
  3. Ji Y, Lu Y, Mills GB. Bayesian models based on test statistics for multiple hypoth- esis testing problems. Bioinformatics 24:943-949, 4/2008.
  4. Miyazaki K, Yamaguchi M, Suguro M, Choi W, Ji Y, Xiao L, Zhang W, Ogawa S, Katayama N, Shiku H, Kobayashi T. Gene Expression Profiling of Diffuse Large B-cell Lymphoma Supervised by CD21 Expression. Br J Haematol 142:562-570, 8/2008.
  5. Li Y, Bekele BN, Ji Y, Cook JD. Dose-schedule finding in phase I/II clinical trials using a Bayesian isotonic transformation. Stat in Med 27:4895-4913, 10/2008.
  6. Hu B, Ji Y*, Tsui KW. Bayesian estimation of inverse dose-response. Biometrics 64:1223-30, 12/2008.
  7. Fanale M, Fayad L, Pro B, Samaniego F, Zachariah G, Nunez C, Ji Y, Younes A. A phase I evaluation of bortezomib in combination with ice (BICE) as treatment for relapsed/refractory classical Hodgkin lymphoma. Annals of Oncology 19:236-236, 2008.


  1. Zhu R, Ji Y, Xiao L, Matin A. Testicular germ cell tumor susceptibility genes from the consomic 129.MOLF-Chr19 mouse strain. Mamm Genome 18:584-595, 8/2007.
  2. Zhang J, Ji Y, Zhang L. Extracting three-way gene interactions from microarray data. Bioinformatics 23:2903-2909, 11/2007.
  3. Ji Y, Li Y, Yin G. Bayesian dose-finding designs for phase I clinical trials. Statistica Sinica 17:531-47, 2007.
  4. Ji Y, Yin G, Tsui K-W, Kolonin M, Sun J, Arap W, Pasqualini R, Do K-A. Bayesian mixture models for complex high-dimension count data. JRSS-C Applied Statistics 56:139-152, 2007.
  5. Ji Y, Li Y, Nebiyou Bekele B. Dose-finding in phase I clinical trials based on toxicity probability intervals. Clinical Trials 4:235-44, 2007.


  1. Kolonin MG, Sun J, Do KA, Vidal CI, Ji Y, Baggerly KA, Pasqualini R, Arap W. Synchronous selection of homing peptides for multiple tissues by in vivo phage display. FASEB J. 20:979-81, 5/2006.
  2. Yin G, Li Y, Ji Y. Bayesian dose-finding in phase I/II clinical trials using toxicity and efficacy odds ratios. Biometrics 62:777-84, 9/2006.
  3. Ji Y, Tsui K-W, Kim KM. A two-stage empirical Bayes method for identifying differentially expressed genes. Computational Statistics and Data Analysis 50:3592- 604, 2006.
  4. Ji Y, Coombes K, Zhang J, Wen S, Mitchell J, Pusztai L, Symmans WF, Wang J. RefSeq refinements of UniGene-based gene matching improve the correlation of expression measurements between two microarray platforms. Appl Bioinformatics 5:89-98, 2006.
  5. Ji Y, Tsui KW, Kim K. A novel means of using gene clusters in a two-step empirical Bayes method for predicting classes of samples. Bioinformatics 21:1055-61, 4/2005.
  6. Ji Y, Wu C, Liu P, Wang J, Coombes KR. Applications of beta-mixture models in bioinformatics. Bioinformatics 21:2118-22, 5/2005.