Jie Chen, PhD

Professor & Division Chief

PhD (Statistics), Bowling Green State University, Bowling Green, OH, 1995

CONTACT INFORMATION
(706) 721-6721
room number AE-1017
jiechen@augusta.edu
Jie Chen
Research

RESEARCH INTEREST

Statistical Change Point Analysis, Applied Statistics, Statistical Inference, Statistics in Bioinformatics, Biostatistics, Statistical Modeling of genomics data and DNA copy number experimental data.

Dr. Chen is specialized in statistical change point analysis, which has a wide spectrum of applications in industrial quality management, climatology, economics and finance, medicine, genetics, etc. She has done extensive research in the area of statistical change point analysis and has co-authored a research monograph on change point analysis which was published by Birkhäuser in year 2000. The expanded second edition of this monograph entitled “Parametric Statistical Change Point Analysis: With Application to Genetics, Medicine, and Finance” was published by Birkhäuser in 2012. In this second edition, new chapters and new applications of statistical change point analysis in genetics and medicine were some of the new features. In addition Dr. Chen has rich collaborative research experience in molecular biology and bioinformatics. She enjoys working with biological and medical researchers on modeling data resulting from various biological experiments. She has participated in collaborative research projects in modeling microarray data for the studies of hematopoietic stem cell differentiation and proliferation, patterns of periodicity in transcriptional programs of mouse somitogenesis, the yeast histone variant, and the gene expression profile of tissues from children with heart diseases, to just name a few. She has developed methodology for modeling array Comparative Genomic Hybridization data (aCGH) in the effort of identifying DNA copy number variants (CNVs) in tumor and cancer cell lines, and is currently working on developing algorithms for detecting CNVs in cancer and tumor cell lines using the next generation sequencing data, modeling DNA methylation data, and RNA-seq data.

Dr. Chen is an elected fellow of the American statistical Association (ASA).

Professor Jie Chen is recently named Editor-in-Chief of the Journal of Applied Statistics by Taylor & Frances, UK  https://www.tandfonline.com/toc/cjas20/current

The Aims and Scope of the Journal can be found at  http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=cjas20

Please contact her for journal related matters at this email address:  JAppliedStats@Augusta.edu

 

teaching

TEACHING AREAS

Undergraduate teaching in Introductory Statistics, and Graduate teachings in Statistics, Biostatistics, Applied Statistical Methods, Mathematical Statistics, Theory of Linear Models, Statistical Inference, Likelihood Principle, Regression Analysis, Data Analysis, and Generalized Linear Models.

publications

SELECTED PUBLICATIONS

  • Deng S, Chen J, Shi H (2021): Integrative analysis of multiple types of genomic data using an accelerated failure time frailty model, Computational Statistics, 36(2), 1499-1532.
  • Lee J, Chen J (2020): A modified information criterion for tuning parameter selection in 1d fused LASSO for inference on multiple change points, Journal of Statistical Computation and Simulation, 90(8), 1496-1519.
  • Lee J, Chen J (2019) A penalized regression approach for DNA copy number study using the sequencing dataStatistical Applications in Genetics and Molecular Biology, 18(4), 20180001, eISSN 1544-6115, DOI: https://doi.org/10.1515/sagmb-2018-0001
  • Chen J, Deng S (2018): Detection of Copy Number Variation Regions Using the DNA-Sequencing Data from Multiple Profiles with Correlated Structure. Journal of Computational Biology, 25, 1128-1140
  • Su Y, Shen X, Chen J, Isales CM, Zhao J, Shi X (2017): Differentially expressed genes in PPARg-deficient MSCs. Molecular and Cellular Endocrinology, 471, 97-104
  • Ji T, Chen J (2015). Modeling the Next Generation Sequencing Read Count Data for DNA Copy Number Variant Study. Statistical Applications in Genetics and Molecular Biology14:361–374.
  • Chen J. Gupta A (2012): Parametric Statistical Change Point Analysis - With Applications to Genetics, Medicine, and Finance, second edition, Birkhauser, New York.
  • Chen J , Wang Y (2009): A Statistical Change Point Model Approach for the Detection of DNA Copy Number Variations in Array CGH Data. IEEE/ACM Transactions on Computational Biology and Bioinformatics 6:529-541.
  • Glynn E, Chen J , Mushegian A (2006): Detecting periodic patterns in unevenly spaced gene expression time series using Lomb-Scargle periodograms. Bioinformatics 22:310-316.
  • Dequeant M, Glynn E, Gaudenz K, Wahl M, Chen J , Mushegian A, Pourquie O (2006): A Complex Oscillating Network of Signaling Genes Underlies the Mouse Segmentation Clock. Science 314:1595-1598.