My research is in the field of applied statistics, particularly in developing and applying methodologies to solve statistical problems that arise in biology. Exciting statistical challenges are continually arising in molecular biology as experimental techniques change rapidly, creating new and more complicated data problems to be addressed. Statistically, this requires the development of appropriate estimation methodology and high-dimensional inference for new types of high-throughput data, as well as multivariate analysis techniques as tools for integration of heterogeneous sources of data. My research interests lie in developing statistical methods for high-dimensional data arising in the field of biology and genetics. I focus on questions of robust estimation and hypothesis testing for high-throughput biological experiments, in particular gene expression microarrays and next generation sequencing. I am also interested in integration of heterogeneous sources of data, where the data can be multiple experimental platforms or, more generally, arbitrary forms of preexisting biological knowledge such as networks or trees. Statistically, I am interested in questions of high-dimensional inference and multivariate analysis -- problems that arise naturally in trying to create a unified understanding of this type of data.
Current Research Collaborations
Classification of Cortical Neurons by Single Cell Transcriptomics
This NIH-supported BRAIN Initiative project aims to provide a suite of technologies for identifying and classifying the diverse cell types in the mammalian nervous system. We are part of multidisciplinary collaboration between 10 research groups at UC Berkeley, headed by John Ngai.
I jointly lead (with Sandrine Dudoit and Nir Yosef) the computational group responsible for the identification of different cell types and of biomarker targets. We are also responsible for developing quality control and analysis techniques for single cell data.
See a more detailed description at the Ngai lab webpage.
Collaborators: John Ngai (Lead PI, MCB), Sandrine Dudoit (Biostatistics), Nir Yosef (CS), Hillel Adesnik (MCB), Helen Bateup (MCB), Dan Feldman (MCB), Jennifer Doudna (MCB, Chemistry, HHMI, LBNL), Dirk Hockemeyer (MCB), Russell Vance (MCB, HHMI)
UC Berkeley press announcement: September 30, 2014 - NIH awards UC Berkeley $7.2 million to advance brain initiative
Epigenetic Control of Drought Response in Sorghum (EPICON)
The Purdom group will lead the computational analysis, specifically to integrate the multiple epigenetic datasets to provide understanding of the interplay of these biological processes. We are looking for a post-doc for this project, see advertisement for more information.
Analysis of Mutation Spectrum of tumors
|Last updated 07/23/2015|