Research Interests: 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).
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.
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 Biology 14:361–374.
Yigiter A, Chen J, An L, Danacioglu D (2015): An online copy number variant detection method for short sequencing reads. Journal of Applied Statistics 42:1556-1571.
Chatterjee A, Ronghe A, Singh B, Bhat N, Chen J , Bhat H (2014): Natural antioxidants exhibit chemopreventive characteristics through the regulation of CNC b-Zip transcription factors in estrogen-induced breast carcinogenesis. J Biochem Mol Toxicol 28:529-538.
O'Brien J, Jr, Kibiryeva N, Zhou X, Marshall J, Lofland G, Artman M, Chen J , Bittel D (2012): Noncoding RNA Expression in Myocardium From Infants With Tetralogy of Fallot. Circulation: Cardiovascular Genetics 5:279-286.
Chen J. Gupta A (2012): Parametric Statistical Change Point Analysis
- With Applications to Genetics, Medicine, and Finance, second edition, Birkhauser, New York.
Zhao J, Chen J , Yang T, Holme P (2012): Insights into the pathogenesis of axial spondyloarthropathy from network and pathway analysis. BMC Systems Biology 6:S4.
Bittel D, Butler M, Kibiryeva N, Marshall J, Chen J , Lofland G, O'Brien J (2011): Gene expression in cardiac tissues from infants with idiopathic conotruncal defects. BMC Medical Genomics 4:1.
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.