howchang@stanford.edu

Dr. Chang is a physician scientist who has pioneered studies of the noncoding genome. He is interested in how the activities of hundreds or even thousands of genes (gene parties) are coordinated to achieve biological meaning. His team will focus on studies of lncRNA-genome interaction and clinical regulome analyses. Lab Website. 

Dr. Curtis pursues systems biology and computational approaches to establish a quantitative and mechanistic understanding of cancer progression. Her research has helped to redefine the molecular map of breast cancer and has led to new paradigms in understanding how human tumors progress. Her team will focus on characterizing regulatory programs in cancer and inferring tumor evolutionary dynamics. Lab Website. 

Dr. Greenleaf is building new tools to leverage the power of high-throughput sequencing and cutting-edge microscopies, and bringing these new technologies to bear against basic biological questions of genomic and epigenomic variation. His group will focus on methods development components of the project, including transposase-based accessible chromatin methods, and higher-order structure determination.  Lab Website.

Dr. Snyder is a worldwide leader in applying omics approaches of genome sequencing, transcriptomics proteomics, metabolomics, DNA methylation and microbiome assays to the analysis of human disease. Dr. Snyder will coordinate the activities of the DNA methylation project and work closely with Drs. Greenleaf and Chang on the mapping of regulation information in personal genomes. Lab Website. 

Dr. Urban is investigating the molecular effects of large genome variants during neuronal development using iPSC model systems and the study of the nature and effects of somatic genome variation in the brain using tissue culture models and primary tissue samples. Dr. Urban will focus on coordinating whole-genome sequence analyses as well as the development of the allele-specific methylome sequencing technology.  Lab Website.

Dr. Wong’s current interest centers on the application of statistics to problems arising from biology, in particular questions concerning gene regulation and signal transduction. The Wong Lab will focus on computational analysis of personal regulome data. Lab Website.