Zhongyuan Chen
   Assistant Professor (Tenure Track)
   Division of Biostatistics
   Medical College of Wisconsin
   Milwaukee, WI 53223
   zhchen  [at] mcw [dot] edu
Research Interests
  • Statistical machine learning and dimension reduction for treatment recommendation (personalized medicine)
  • Statistical methods and large-scale data analysis for cancer genomic and genetic data
  • Bioinfomatics and computational biology for big data of cancer
  • Causal inference: heterogeneous treatment effect estimation; causal effects estimation for high-dimensional regression
  • Statistical analysis for randomized numerical algorithms
  • Applications to biomedical science and clinical trials
Background
   Ph.D., Statistics, Rice University, USA
 
Papers (Google Scholar Citations)
  Preprints to Be Submitted
  1. Z. Chen and F. Liang. Causal effects estimation for high-dimensional regression. Preprint to be submitted to Journal of American Statistical Association, (2024).
  2. Z. Chen, H. Liang, and P. Wei. Efficient randomized low-rank parameter pre-selection for pathway-based test methods. Preprint to be submitted to Computational Statistics and Data
    Analysis, (2024).
  3. Z. Chen. Improving a randomized indicator method for symmetric eigenvalue solution. Preprint to be submitted to Computational Statistics and Data Analysis, (2024).
  Published/Submitted
  1. J. Dong, S. Arsang-Jang, T. Zhang, Z. Chen, Y.T. Bolon, S. Spellman, R. Urrutia, P. Auer, W. Saber. Prognostic impact of donor mitochondrial genomic variants in myelodysplastic syndrome after stem-cell transplantation.
    Submitted (2024).
  2. Z. Chen, J. Sun, and J. Xia. A robust randomized indicator method for accurate symmetric eigenvalue detection.
    Submitted. (PDF) (2023).
  3. Z. Chen, H. Liang, and P. Wei. Data-adaptive and pathway-based tests for association studies between somatic mutations and germline variations in human cancers.
    Genetic Epidemiology, 47,     617--636 (2023). (Journal link, PDF)
  4. Z. Chen and J. Xie. Estimating heterogeneous treatment effects versus building individualized treatment rules: Connection and disconnection.
    Statistics & Probability Letters, 199, 109854  (2023) (Journal Link, PDF)
  5. Z. Chen, Z. Wang, Q. Song, J. Xie. Data-guided Treatment Recommendation with Feature Scores.
    Statistica Sinica, 32, 2497--2519 (2022). (Journal link, PDF)
  6. X. Song, H. Chen, C. Zhang, Y. Yu, Z. Chen, H. Liang, et al. SRC-3 inhibition blocks tumor growth of pancreatic ductal adenocarcinoma.
    Cancer Letters, 442, 310--319 (2019). (Journal link, PDF)
  7. X. Peng*, Z. Chen*, F. Farshidfar*, et al. Molecular characterization and clinical relevance of metabolic expression subtypes in human cancers.
    Cell Reports, 23, 255--269 (2018). (*co-first authors contributed equally) (Journal link, PDF)
  8. Z. Ge, J. S. Leighton, Y. Wang, X. Peng, Z. Chen, H. Chen, et al. Integrated genomic analysis of the ubiquitin pathway across cancer types.
    Cell Reports, 23, 213--226 (2018). (Journal link, PDF)
  9. Y. Wang, X. Xu, D. Maglic, M. T. Dill, K. Mojumdar, P. K. Ng, K. J. Jeong, Y. H. Tsang, D. Moreno, V. H. Bhvana, X. Peng, Z. Ge, H. Chen, J. Li, Z. Chen, H. Zhang, L. Han, D. Du, C. J. Creighton, and G. B. Mills. Comprehensive molecular characterization of the Hippo signaling pathway in cancer.
    Cell Reports, 25, 1304--1317 (2018). (Journal link, PDF)
  10. J. B. Pakish, Q. Zhang, Z. Chen, H. Liang, et al. Immune microenvironment in microsatellite-instable endometrial cancers: Hereditary or sporadic origin matters.
    Clinical Cancer Research, 23, 4473--4481 (2017). (Journal link, PDF)
  11. C. Li, S. Wang, Z. Xing, A. Lin, K. Liang, J. Song, Q. Hu, J. Yao, Z. Chen, et al. A ROR1-HER3-LncRNA signaling axis modulates the Hippo-YAP pathway to regulate bone metastasis.
    Nature Cell Biology, 19, 106--119 (2017). (Journal link. PDF)
  12. Z. Chen and C. M. Kearney. Nectar protein content and attractiveness to Aedes aegypti and Culex pipiens in plants with nectar/insect associations.
    Acta Tropica, 146, 81--88 (2015). (Journal link, PDF)
  13. Z. Chen, S. Lu, and J.-R. Huang. Metabolic engineering and applications of plant carotenoid biosynthesis.
    Chinese Bulletin of Life Sciences, 23, 205--211 (2011).
  Abstracts
  1.  T. Zhang , P. Auer , S. Spellman, J. Dong, Z. Chen, W. Saber, and Y. Bolon. Novel Molecular Biomarkers Prognostic of Relapse after Allogeneic Hematopoietic Stem Cell Transplantation
    in Patients with Myelodysplastic Neoplasms (MDS). Tandem Meetings: Transplantation & Cellular Therapy Meetings of ASTCT and CIBMTR, (2023)
  2. D. Scott, Z. Chen, and L. B. Kreuziger. Unfractionated heparin use in the setting of acute pulmonary embolism. To be submitted to Thrombosis & Hemostasis Summit of North America
    (THSNA), (2024)
  In Preparation
  1. Z. Chen. Data-adaptive and pathway-based tests for the association studies between myelodysplastic syndromes patients’ overall survival and germline variants, (2024)
  2. Z. Chen. Improving the accuracy of statistical prediction models of myelodysplastic syndromes patients’ overall survival via integrative genetic and genomic data, (2024)
  3. Z. Chen, P. Auer, C.W. Lin, and K.W. Ahn. Integrative genomic/genetic and survival data guided treatment recommendations via feature score for myelodysplastic syndromes patients, (2024)
  4. R. Ahmed, P. Anyanwu, Z. Chen, N. Shah, M. Hamadani, W. Longo, S. Devata, J. Pruett, J. Connelly, J. Bovi, M. Siker, C. Schultz, T. Fenske. Real-world experience with RTOG 0227 induction for first line therapy of primary CNS lymphoma (PCNSL), (2024)
  5. K. Gordon, D. Cao, Z. Chen, Y. Yang, P. Auer. Safety and incidence of malignancy of biologic therapy biologic therapy for psoriasis patients with a prior cancer diagnosis, (2024)
  6. Z. Chen and J. Xie. Biomarker selection for treatment recommendation by Sliced Inverse Regression via Lasso.
  7. Z. Chen and J. Xie. Statistical analysis in progression event of pancreatic and colorectal cancer using cancer genomic and clinical data.
  PhD Thesis
  1. Z. Chen. Association Studies in Human Cancers: Metabolic Expression Subtypes and Somatic Mutations/Germline Variations. Rice University.
 
Presentations and Conference Participation
     Invited Presentations
  • Seminar, Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, invited talk, September 2023
  • Minisymposium in 10th International Congress on Industrial and Applied Mathematics, Tokyo, invited talk, August 2023
  • Seminar, Department of Statistics, Purdue University, West Lafayette, invited talk, April 2023
  • Seminar, Division of Biostatistics, Medical College of Wisconsin, online, invited talk,  February 2023
  • Seminar, Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, invited talk, February 2023
  • Seminar, Department of Statistics, Oklahoma State University, Stillwater, invited talk, February 2023
  • Seminar, Department of Mathematics and Statistical Science, University of Idaho, Moscow, invited talk, January 2023
  • Seminar, Department of Mathematical Sciences, Purdue University, Fort Wayne, invited talk, December 2022
  • Seminar, Division of Biostatistics, Department of Population Health Sciences, University of Utah, online, invited talk, November 2022
  • INFORMS Annual Meeting 2022, Indianapolis, invited talk (Data-guided Treatment Recommendation With Feature Scores), October 2022
  • Copper Country Workshop on Applied Mathematics, Statistics and Data Sciences, Michigan Technological University, invited talk (Reliable Statistical Indicator Strategies for Numerical Computations), July 2022
  • Conference on Random Matrix Theory and Numerical Linear Algebra, University of Washington, invited poster (A Robust Randomized Indicator Method for Fast and Accurate Symmetric Eigenvalue Solution), June 2022
  • 2021 Joint Statistical Meetings, online, invited poster (Data-guided Treatment Recommendation with Feature Scores), August 2021
  • Seminar, School of Biomedical Informatics and School of Public Health, University of Texas Health Science Center at Houston, invited talk (Association Studies in Human Cancers: Metabolic Expression Subtypes, Somatic Mutations/Germline Variations, and Beyond), February 2019
  • 2018 Annual Symposium, Society of Chinese Bioscientists in America - Texas Chapter, Houston, invited talk (Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers), May 2018
     Other Presentations and Conference Participation
  • Group seminar, Department of Statistics, Purdue University, West Lafayette, November 2022
  • 9th International Purdue Symposium on Statistics, Purdue University, June 2018
  • Machine Learning Workshop, Rice University, Jan 2017
  • International Conference on Intelligent Biology and Medicine (ICIBM), Rice University, December 2016
  • TCGA PanCanAtlas Houston F2F Conference, Houston, November 2016
  • Texas Regional Immunology Conference, MD Anderson, November 2016
  • 2nd Annual Vaccine Biotechnology Conference, MD Anderson Cancer Center, October 2013
  • Baylor Biomedical Retreat, Baylor University, poster (Constructs and Toxins for Mosquitocidal Nectar Plants), March 2013
Teaching
     At Medical College of Wisconsin
  •  04224, Biostatistical Computing (Biostatistics PhD Program), Fall 2023
    At Purdue University  
  • STAT 512, Applied Regression Analysis (Graduate level), Fall 2019, Fall 2020, Fall 2021
  • STAT 513/IE 530, Statistical Quality Control (Graduate level), Spring 2020, Spring 2021, Spring 2022