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Publications: NCBI Bibliography, SciVal, Google Scholar
Lab description:
We are a computational
biology group in the Department of Bioinformatics and Computational Biology
at UT MD Anderson Cancer Center in Houston, Texas.
We are interested in
developing computational methods to systematically and accurately
characterize the genomics and the transcriptomics of
human cell populations using high throughput
sequencing technology. For example, we have developed approaches that successfully
discovered and reconstructed structural variation in a variety of
cancer genomes. We are also interested in developing integrative
approaches that help understand the etiology of cancer. We are
actively involved in several large-scale genomics projects such as the
Cancer Genome Atlas (TCGA) and the 1000 Genomes projects. Since 2012, we
have worked with the Khalifa Institute of Personalized Cancer Therapy to
establish routine genome sequencing at MD Anderson cancer center.
PI biography:
Dr. Ken Chen (h-index: 28,
2015) received his B.E. from Tsinghua University (Beijing), Ph.D. from
University of Illinois at Urbana-Champaign, and postdoctoral training from
University of California at San Diego. From 2005 to 2011, he worked for
Washington University School of Medicine in St. Louis as a senior scientist and
a research faculty. Having a background in machine learning, statistical signal
processing, and cancer genomics, his primary goal is to develop computational
tools to analyze and interpret human genomics and clinical data towards the
realization of genomic medicine. Dr. Chen has designed, developed, and
co-developed a set of computational tools such as BreakDancer,
TIGRA, CREST, BreakTrans, BreakFusion,
PolyScan, SomaticSniper, VarScan, TransVar, novoBreak and Monovar that have
been widely applied to characterize individual and population genomics in
various large-scale next-generation sequencing projects such as those in the
Cancer Genome Atlas (TCGA) and the 1000 Genomes Project. He is
particularly interested in comprehensively and accurately constructing the
genomes and the transcriptomes of various cancer cell
populations towards understanding the heterogeneity and the evolution of cancer
as a consequence of genetics and environment. He is also interested in
developing integrative approaches to identify biomarkers that are useful for
diagnosis and prognosis. He has served as the Director of Bioinformatics
for the Khalifa Institute of Personalized Cancer Therapy
since 2012.
Research areas:
1 Computational approaches for next/third generation
sequencing data analysis
2 Detection of structural and copy number variation in
normal and cancer genomes
3 Accurate assembly of novel DNA or
RNA sequence variants
4 Discovery and genotyping of sequence variants in heterogenous sample or population
5 Graphic approaches for RNA-seq
analysis
6 Integrative characterization of genome and transcriptome
7 Computational approaches for single cell genomics
8 High quality bioinformatics tools for clinical
sequencing and clinical decision support
9 Cancer genetic driver prediction for biomarker and
therapeutic target discovery
10 Computational cancer
immunogenomics