"The nature of biological data has changed dramatically in the past decade, and our success as a company depends on how well we can derive insights from extremely complex, large-scale data sets. We apply rigorous scientific and engineering principles to the handling of data to ensure that they remain meaningful at every scale."
I completed my BA in Biochemistry at UC Berkeley, and received an MS in Statistics and Ph.D. in Biological Sciences from the University of Texas at Austin, where I studied microbial evolution and computational systematics. I continued in my computational turn with a postdoc in David Botstein’s lab at Stanford University Medical School’s Department of Genetics, followed by a research fellowship at the Lewis-Sigler Institute for Integrative Biology at Princeton. In 2006 I joined Genentech as a scientist to support research programs in Translational Oncology and Tumor Biology & Angiogenesis.
With the advent of High Throughput Sequencing, I formed and led a new Scientific Computing Group to implement processes and methods for effectively using genome-scale data of increasing volume and complexity. I have continued in this vein as a primary contributor to the success of the Human Genetics Initiative, and have helped to define both gRED’s Informatics Strategy and gRED’s relation to Roche-wide data science initiatives.
The role of my group (now called Data Science and Statistical Computing), is becoming especially important as the company moves to make better research use of data from clinical trials. My team and I will continue to be at the forefront of our efforts to develop personalized healthcare solutions for the benefit of patients.
My group, Data Science & Statistical Computing, is a new organization with the mission of enabling the research use of complex data at vast scale. We comprise a mixture of scientists and engineers, with extensive biological as well as statistical and computational experience.
As director of the group my job is to identify the ways in which computational biologists and life scientists collect, process, analyze and visualize complex data sets, and to enable the processes and technology to make this as effective as possible. I also help to set and implement the informatics strategy for Research, and serve as a data and analytics conduit between Genentech and Roche.