Qing Nie

picture of Qing  Nie

Chancellor's Professor, Mathematics
School of Physical Sciences

Chancellor's Professor, Developmental & Cell Biology
School of Biological Sciences

Chancellor's Professor, Biomedical Engineering
The Henry Samueli School of Engineering

Ph.D., The Ohio State University, 1995

Phone: (949) 824-5530
Fax: (949) 824-7993
Email: qnie@uci.edu

University of California, Irvine

Research Interests
Computational and Systems Biology; Machine Learning; Developmental Biology; Stochastic Dynamics; Scientific Computing and Numerical Analysis
Academic Distinctions
Chancellor's Professor, UC Irvine, 2017-
Chancellor's Fellow, UC Irvine (2005-2008)
2017 - present: Chancellor's Professor, Dept of Mathematics and Dept of Developmental & Cell Biology, UC Irvine
2005-2016: Professor, Department of Mathematics, UC Irvine
2002-2005: Associate Professor, Department of Mathematics, UC Irvine
1999-2002: Assistant Professor, Department of Mathematics, UC Irvine
1997-1999: L.E. Dickson Instructor, Department of Mathematics, University of Chicago.
Awards and Honors
Fellow, American Association for the Advancement of Science (AAAS)
Fellow, American Physical Society (APS)
Fellow, Society for Industrial and Applied Mathematics (SIAM)
Short Biography
Director, NSF-Simons Center for Multscale Cell Fate Research (2018 - )
Associate Director, UCI PhD Program on Mathematical, Computational, and Systems Biology (MCSB) (2009 - )
Zhou P, S Wang, T Li, Q Nie. Dissecting transition cells from single-cell transcriptome data through multiscale stochastic dynamics, Nature Communications, 12:5609, 2021
Jin S, C. Guerrero-Juarez, L. Zhang, I. Chang, R. Ramos, C. Kuan, P. Myung, K. Plikus*, Q. Nie*. Inference and analysis of cell-cell communication using CellChat. Nature Communications, 12(1088), 2021. *:Co-corresponding authors
Zhang L, Q. Nie. scMC learns biological variation through the alignment of multiple single cell genomics datasets. Genome Biology, 22:10, 2021
Cang Z, Y. Wang, Q. Wang, K. Cho, W. Holmes, Q. Nie. A multiscale model via single-cell transcriptomics reveals robust patterning mechanism during early mammalian embryo development. PLoS Computational Biology, 17(3) e1008571, 2021.
Fu L., L Zhang, E. Dollinger, Q. Peng, Q. Nie*, X. Xie*. Predicting transcription factor binding in single cells through deep learning. Science Advances, 6:eaba9301, 2020. *:co-corresponding author.
Cang Z and Q. Nie. Inferring spatial and signaling relationships between cells from single cell transcriptomic data. Nature Communications, 11(2084), 2020.
Jin, S*., L. Zhang*, Q. Nie. scAI: an unsupervised approach for the integrative analysis of parallel single-cell transcriptomic and epigenomic profiles. Genome Biology, 21(1):25, 2020. * co-first authors
Professional Societies
Society for Applied and Industrial Mathematics (SIAM)
American Physical Society (APS)
American Association for the Advancement of Science (AAAS)
American Mathematical Society (AMS)
Research Centers
NSF-Simons Center for Multiscale Cell Fate Research
Center for Complex Biological Systems
Last updated