Honors & Awards
George Beadle Award, GSA (2019)
Elected Member, American Academy of Science (2015)
Stanford B. Ascherman Professor, Stanford (2011)
Pioneer Award, Human Proteome Organization (2009)
CT Medal of Science, Connection Academy of Science (2007)
Pew Scholar Award, Pew Foundation (1987-1991)

We are presently in an omics revolution in which genomes and other omes can be readily characterized. Our laboratory uses a variety of approaches to analyze genomes and regulatory networks. Our research focuses on yeast, an ideal model organism ideally suited to genetic analysis, and humans.

1) Transcriptomes
To annotate genomes, we developed RNA sequencing for annotation the yeast and human transcriptomes. We discovered that the eukaryotic transcriptome is much more complex than previously appreciated and that embryonic stem cells have more transcript isoforms than differentiated cells.

2) Transcription Factor Binding Networks
We have also developed methods for mapping transcription factor binding sites through the genome. We used this to develop regulatory maps and have been using this to help decipher the combinatorial regulatory code – which factors work together to regulate which genes. Using this approach we have mapped out pathways crucial for metabolism and inflammation.

3) Integrated Regulatory Networks
In addition to transcriptional factor binding networks we have also been mapping phosphorylation and metabolite-protein interaction networks. These studies have revealed novel global regulators and key points in integrated regulatory networks.

4) Variation
We have been analyzing differences between individuals and species at two levels: DNA sequence variation and regulatory information variations. We developed paired end sequencing for humans and found that humans have extensive structural variation (SV), i.e. deletions, insertions and inversions. This is likely to be a major cause of phenotypic variation and human disease. In addition, by mapping binding sites difference among different yeast strains and humans, we have found that individuals differ much more in their regulatory information than in coding sequence differences. We can correlate these differences with those in SNPS and SVs, thereby associating noncoding DNA differences with regulatory information.

5) Human Disease
Finally, we are applying omics approaches of genome sequencing, transcriptomics proteomics metabolomics, DNA methylation and microbiome assays to the analysis of human disease. These integrative omics approaches are being applied to help understand the molecular basis of disease and the development of diagnostics and therapeutics.