Ken Chen

Ken Chen is a computational biologist whose work spans cancer genomics, single-cell transcriptomics, and computational oncology. He is a tenured professor in the Department of Bioinformatics and Computational Biology at the University of Texas MD Anderson Cancer Center, where he directs bioinformatics programs in personalized cancer therapy and single-cell genomics. He is known for developing BreakDancer , a computational algorithm for detecting genomic structural variation, and for contributing bioinformatics methods to major international consortia including The Cancer Genome Atlas (TCGA), the 1000 Genomes Project, and the Human Cell Atlas.

Early life and education

Chen studied precision instrumentation at Tsinghua University in Beijing, earning a B.Eng. in 1996. His undergraduate training combined mechanical engineering, measurement systems, and quantitative methods.

He pursued a Ph.D. in Electrical and Computer Engineering at the University of Illinois Urbana-Champaign under the supervision of , completing it in 2004. During his doctoral studies, his focus shifted from signal processing and speech recognition toward computational methods for analyzing complex biological data. He also held visiting researcher positions at Microsoft Research Asia in Beijing (2001) and at the Center for Language and Speech Processing at Johns Hopkins University (2004).

Career

Following his doctorate, Chen completed postdoctoral training in Biophysics and Biochemistry at the University of California San Diego (2005). He then joined the Genome Institute at Washington University in St. Louis, where he worked under Elaine Mardis from 2005 to 2011. During this period, he contributed to large-scale cancer genome sequencing work, including the studies of the first cancer acute myeloid leukemia genome , and co-developed several variant-calling tools such as BreakDancer .

In 2011, Chen joined the University of Texas MD Anderson Cancer Center as an assistant professor in the Department of Bioinformatics and Computational Biology. He was promoted to associate professor in 2016 and to full professor in 2021.

At MD Anderson, Chen serves as director of bioinformatics for the Institute for Personalized Cancer Therapy and co-director of the GSBS Quantitative Science program. He taught in GS01 1143 "Introduction to Bioinformatics" since 2012. He chairs the Gulf Coast Single Cell and Spatial Omics Consortium and holds an adjunct faculty appointment in computer science at Rice University. His laboratory has received independent research funding from the National Institutes of Health (NIH), Advanced Research Projects Agency for Health (ARPR-H), the Cancer Prevention and Research Institute of Texas (CPRIT), and the Chan Zuckerberg Initiative.

Research

Chen's laboratory develops computational methods for analyzing large-scale genomic, single-cell, and spatial transcriptomic data, with applications spanning cancer biology, tumor immunology, and precision medicine. bindSC, for cross-platform integration of single-cell datasets including scRNA-seq, scATAC-seq, and spatial omics.; METAFlux, for metabolic flux analysis of single-cell and spatial data. Other tools from the lab include MEDALT, for copy number phylogeny inference of single-cell and spatial data; and CellTrek, a method that integrates single-cell RNA sequencing with spatial transcriptomics data to map individual cells to their physical locations within tissue sections.

Immuno-oncology and cell therapy

Chen's lab has expanded into tumor immunology and computational support for cancer clinical trials. and discovery of effector regulatory T cells depletion as a potential mechanism of Immune checkpoint therapy response in Human papillomavirus infection (HPV+) head and neck cancer patients. His lab has also developed agent-based computational models to simulate cellular dynamics in adoptive cell therapy.

Applied machine learning and artificial intelligence

Drawing on his doctoral background in machine learning and signal processing, Chen's lab applies artificial intelligence methods to genomics and clinical medicine. The lab has also developed multimodal deep learning models for clinical prediction, including a longitudinal model for forecasting acute kidney injury and resource utilization in ICU patients.

Awards and honors

Fellow, American Institute for Medical and Biological Engineering (AIMBE), 2025 Celebration of Faculty Excellence in Research, University of Texas MD Anderson Cancer Center, 2024 Senior member, The Institute of Electrical and Electronics Engineers (IEEE), 2009 Elected member, Sigma Xi, Scientific Research Honor Society Elected member, Phi Kappa Phi, Honor Society

Selected publications

Chen has authored or co-authored over 220 peer-reviewed articles (Scopus h-index: 86; total citations: 92,000). The following is a selection of high-impact works spanning his career.

Structural variant detection

Cancer genomics

Single-cell and spatial transcriptomics

Immuno-oncology and cell therapy

Applied machine learning and artificial intelligence

Multi-omics and translational cancer biology