Studied biochemistry and did postgraduate work in computer science at Harvard College. Received PhD in cell biology from Yale University.
After postdoctoral work at the University of Geneva, joined Cellular Genomics to build the companyís bioinformatics program.
Outside interests tend to center around his young son, Sam, though he continues to be an avid backcountry skier.
QWhat are the biggest challenges bioinformatics must overcome?
AThe need to integrate data from a broad range of different sources is huge. At Cellular Genomics we''''re generating DNA sequence data, 2D gel images, mass spec-derived protein identifications, immunofluorescence images, microarray-based gene expression data, and cell-based assay data. Add to this the analysis performed on each data set, and it''''s easy to see how things can get very complicated, very quickly. Integration of these data is the first step toward synthesizing it into the knowledge required to drive drug discovery.
Just as critical as data integration, though, is the integration of computational methods into the biology as it is practiced in the laboratory. A biologist with a solid understanding of the analytical tools that can be applied to a particular problem will be able to design better experiments to answer the most critical questions. A computer scientist with an understanding of biology is more likely to develop tools that will reveal pharmacologically relevant information in experimental data.
QWhat do you see as the most important task for bioinformatics to address beyond genome sequencing?
AGenomic sequencing was a relatively well-structured problem compared with the next challenge: identifying proteins produced by the genes and elucidating the pathways in which they function. We are a long way from knowing how many proteins our genes encode, let alone where they are expressed in the body and, most importantly, what functions the proteins perform. By elucidating the pathways in which proteins act, we can identify additional disease-relevant targets to pursue, as well as to estimate the clinical implications of a drug against a particular target. Bioinformatics will play an essential role in all steps of this process, from enabling proteomics efforts to identify proteins and their interaction partners, to mapping the signaling pathways.
QWhat bioinformatics software do you use?
AInitially, we are primarily using third-party software, but we have begun the process of customizing solutions to meet our needs and the needs of our future partners. Our scientists use Vector NTI for desktop work, and we have recently partnered with InforMax and Viaken to deploy the GenoMax enterprise-wide bioinformatics platform. We are working with Applied Biosystems to develop a LIMS infrastructure for all of our laboratory processes. Finally, we are developing databases and customizing bioinformatics tools to enable our pathway mapping, target validation, and drug discovery work.
QWhose microarrays do you use?
AWe''''re bringing a GeneChip expression analysis system from Affymetrix in-house, and have recently signed a Biotechnology Access Program agreement with Affymetrix for ongoing chip access.
QHow is your bioinformatics unit organized within the framework of Cellular Genomics?
ABioinformatics at Cellular Genomics falls within the biological research section. While there is a lot of overlap between IT and bioinformatics here, we see bioinformatics as a critical research tool. We want to be sure that our bioinformatics efforts facilitate research.
QWhat projects are you working on now?
AOne major project at the moment is infrastructure development. The company is in a rapid growth phaseówe are nearing completion of a proteomics/ mass spec facility, a microarray facility, and a sequencing facilityóall of which require both LIMS and analytical support. We are also developing databasesóto build a knowledge base to help guide our scientific efforts, as well as pathway mapping databases based on our results. We are also developing tools with which to leverage the knowledge generated in our target validation process to the drug discovery process.