Professor of Medicine & Co-Director of Cancer Bioinformatics
My focus is on bioinformatics analysis of molecular profiling data, which may include mRNA expression, microRNA expression, protein expression, DNA methylation, or DNA copy number. Fundamentally, my work seeks to obtain meaningful information from large scale molecular datasets regarding questions relevant to improving cancer diagnosis and treatment. This often involves integration of molecular profiling results from different sources. Among other things, I have participated extensively in The Cancer Genome Atlas (TCGA) and Pan-Cancer Analysis of Whole Genomes (PCAWG) consortiums, multi-institutional efforts to systematically characterize the genomic changes that occur in cancer.
- Understanding the molecular basis of cancer through genomics and proteomics
- Integrative analysis of diverse molecular data types
- Mining public genomic databases
- Noncoding somatic DNA alterations
Baylor College of Medicine
Defining the Global Impact of Somatic Structural Variation on the Transcriptome of Human Pediatric Brain Cancers
Somatic structural variants (SSVs) are mutations arising in tumors that involve large segments of DNA. Using data from the Pediatric Brain Tumor Atlas, researchers will identify SSV patterns in pediatric cancer types that could lead to new therapies.
All Brain Tumor Types
Proteogenomic Characterization of 2002 Human Cancers Reveals Pan-Cancer Molecular Subtypes and Associated Pathways
This pan-cancer survey utilizing RNA sequencing data from CBTN helps to deepen the understanding of how brain tumors develop and grow.
Yiqun Zhang, Fengju Chen, Darshan S. Chandrashekar, Sooryanarayana Varambally, Chad J. Creighton
Systematic Identification of Non-coding Somatic Single Nucleotide Variants Associated with Altered Transcription and DNA Methylation in Adult and Pediatric Cancers
Whole-genome sequencing combined with transcriptomics can reveal impactful non-coding single nucleotide variants (SNVs) in cancer. Here, we developed an integrative analytical approach that, as a first step, identifies genes altered in expression or DNA methylation in association with nearby somatic
Fengju Chen, Yiqun Zhang, Chad J. Creighton