Department of Computer Science and Technology
Email: tingchen AT tsinghua dot edu dot cn
Ph.D. (1997), Computer Science Department, SUNY at Stony Brook.
B.E. (1993), Department of Computer Science and Technology, Tsinghua University, Beijing.
Director, Center for Big Data Research in Health and Medicine, Institute of Data Science, Tsinghua University, 2016-Present.
Areas of Research Interests/ Research Projects
Computational Biology and Biomedical Informatics
Dr. Ting Chen is currently Professor of computer science at Tsinghua University, and director of Center for Big Data Research in Medicine and Health, Institute of Data Science. He is also a faculty member at Beijing National Laboratory of Information Science and Technology. He graduated from Tsinghua University in 1993 with B.E. in computer science, and received his Ph.D. in computer science at SUNY Stony Brook in 1997. He was a lecturer of genetics at Harvard University from 1997 to 2000, and then became an assistant professor, associate professor and full professor of biological sciences and computer science at the University of Southern California (USC) before he joined Tsinghua University.
His research interests are in the areas of computational biology/bioinformatics, medical informatics, algorithms, and statistical learning. His current research topics include (1) medical data analysis and intelligent medicine, (2) single-cell RNA sequencing data analysis, (3) human genotype and phenotype association, and (4) human microbial interactions, functions and identifications. He has published over 100 papers, many in the top journals including Science, PNAS, Nature Communications, Cell Systems, Genome Research, American Journal of Human Genetics, Genome Biology, and Nucleic Acid Research. His publications have >10000 citations (Google Scholar).
He received the Sloan Research Fellowship in 2004.
1.Liu Z, Lou H, Wang H, Xie K, Chen N, Aparicio O, Zhang M, Jiang R* andChen T*(2017) Reconstructing Cell Cycle Pseudo Time-Series via Single-cell Transcriptome Data. Nature Communications. 2017 Jun 19;8(1):22. DOI: 10.1038/s41467-017-00039-z
2.Yang Y, Chen N*,Chen T*(2017). mLDM: a new hierarchical Bayesian statistical model for sparse microbial association discovery. Cell Systems. Volume 4, Issue 1, p129–137.e5, 25 January 2017.
3.Jiang L, Chen N* andChen T*(2016) DACE: A Scalable DP-means algorithm for clustering extremely large sequence data. Bioinformatics. doi:10.1093/bioinformatics/btw722.
4.Zeng F, Jiang R* andChen T*(2013) PyroHMMSNP: a SNP caller for Ion Torrent and 454 Sequencing Data. Nucleic Acid Research. 1-13, doi:10.1093/nar/gkt372.
5.Lehmann K andChen T*(2012) Exploring functional variant discovery in non-coding regions with SInBaD. Nucleic Acid Research, August 31, 2012 doi:10.1093/nar/gks800.
6.Hao X, Jiang R, andChen T*(2011) Clustering 16S rRNA for OTU prediction: a method of unsupervised Bayesian clustering. Bioinformatics. 2011 Mar 1;27(5):611-8. Epub 2011 Jan 13.
7.Chen Y, Souaiaia T, andChen T*(2009) PerM: Efficient Mapping of Short Sequencing Reads with Periodic Full Sensitive Spaced Seeds. Bioinformatics. 25(19):2514-21.
8.Wang L, Sun F andChen T*. (2008) Prioritizing functional modules mediating genetic perturbations and their phenotypic effects: a global strategy. Genome Biology. 9:R174, 2008.
9.Jiang R, Yang H, Kuo J CC, Sun F andChen T*. (2007) Sequence-based prioritization of nonsynonymous single nucleotide polymorphisms for the study of disease mutations. American Journal of Human Genetics. 2007 Aug;81(2):346-60.
10.Jiang R, Tu Z,Chen T*and Sun F*. (2006) Network Motif Identification in Stochastic Networks. The Proceeding of National Academy of Sciences (PNAS). 2006. vol 103 no 2 page 9404-9. (* corresponding authors)