Ken Chen Laboratory
Ken Chen, Ph.D.
Principal Investigator
Areas of Research
- Artificial Intelligence
- Bioinformatics Research
- Cancer Genomics
- Computational Biology Research
- Immunotherapy Research
- Single-Cell Genomics Research
- Systems Biology
- Tumor Heterogeneity
Welcome to the Ken Chen Lab (KClab) site! KClab at MD Anderson focuses on developing and delivering cutting-edge computational approaches for characterizing and interpreting heterogeneous tumor specimens. In the context of translational research, the lab focuses on identifying molecular targets and algorithms that are potentially useful for personalized diagnosis and medicine. In addition to developing computational tools, the lab has applied and supported bioinformatics analyses and hypothesis generation/testing in The Cancer Genome Atlas, Human Cell Atlas, PreCancer Atlas, Moon Shots Program®, Cancer Target Discovery and Development (CTD2), and more. The lab has independent funding from the National Institutes of Health (NIH), Cancer Prevention and Research Institute of Texas (CPRIT), and Chan Zuckerberg foundations and also collaborates widely with oncologists, biotechnologists and cancer immunologists.
The Chen Laboratory is currently interested in the following research areas:
Single-cell transcriptomics, multiomics and statistics, such as
- bindSC: integrating datasets obtained from different single-cell technologies including scRNA-seq, scATAC-seq, spatial omics and CyTOF
- SCMER: selecting most informative features/genes/proteins in a single-cell dataset.
Tissue clonal heterogeneity and evolution modeling:
- Texomer, allele-specific copy number and RNA expression deconvolution of autologous DNA/RNA-seq data
- SiFit, single-cell phylogenetic tree from somatic mutations detected in single cell sequencing data
- MEDALT, single-cell phylogenetic tree from somatic copy number alterations detected in single cell sequencing data
Tumor-Immune systems biology (particularly, CAR cell therapy)
Artificial intelligence in cancer research:
- Protein structural-modeling (e.g., AlphaFold2)
- Algorithms for big biomedical data analysis
- Regulatory network, e.g., DNA->RNA, RNA->protein
- Relation extraction from biomedical literature
Structural and copy number alterations in human genomes, including:
- BreakDancer, structural variant detection from NGS data
- NovoBreak, de novo breakpoint assembly from NGS data
Systems/network biological approaches for molecular target discovery
Clinical applications (including trial data analysis) and decision support:
- ClinSeK, alignment-free, targeted genotyping/clonality characterization of clinical mutations
- TransVar, trans-level annotation of mutations across DNA, RNA and proteins.
VISIT our github: https://github.com/KChen-lab
Postdoctoral and research assistant positions for graduates and undergraduates are often available. Please feel free to email Dr. Ken Chen to schedule a discussion.
Life in the Chen Lab
Christmas Party 2022
Zoom meetings (Covid-19 days) - August 2020
Lunch at Cooking Girls - December 2019
Night at Museum - January 2019
Group Dinner Hotpot - April 2018
Department Group Photo - 2015