AT A GLANCE Holds a Bachelor’s degree in biology and completed the first two years of a PhD program at the Drosophila Genome Center at the University of California, Berkeley. Likes reading, wine, and skiing. Was captain of the UC Berkeley ski team.
Q Where will bioinformatics be in five years? Ten years?
A I really believe that New Science requires new business models. Many of the stand-alone bioinformatics businesses of today will become part of an integrated group of technologies that molecular biologists will be using to conduct research. I expect that pharmaceutical and biopharmaceutical partners are more likely in the future to want results and not simply software. Over the next few years, they’re going to come to the realization that they do not have the expertise or the luxury of time to install and constantly update their ability to study the genome computationally.
Q What are the biggest challenges bioinformatics must overcome?
A One important challenge we face as computational biologists is that we are asking our customers, big pharmaceutical and biotechnology companies, for example, to change the way they make discoveries in a very fundamental way. Previous new technologies adopted in the pharmaceutical industry were aimed at improving efficiencies in drug discovery, but the tasks were fundamentally unchanged from things that these companies have been doing for decades. This is not the case with our computational approaches that represent revolutionary new ways to engage in drug discovery and development.
Q Which databases do you use? Public, proprietary or third party.
A We primarily use our own in-house database for storing and querying genomic data. But this is a very complex process that involves getting data from many external sources and integrating with external databases. We use SQL-based DBMSes, we have our own proprietary database architecture and applications and we use the data from many different external data sources. We, of course, use GenBank, SwissProt, EMBL, and others. We generate our own database of all of the genes in the human genome.
Q What bioinformatics software do you use? Do you use in-house developed or third party software?
A We use our own and others. When we started the company in 1996, very few folks were even thinking about visualizing whole genomes so we went ahead and wrote our own genome annotation tools. We use external tools like Blast, PSI-Blast, RepeatMasker, and we use Lion Bioscience’s SRS for accessing some external data sources.
Q How large is your bioinformatics staff? Is the organization hiring additional bioinformatics staff?
A We all use bioinformatics and genomics to do computational biology science. We are currently 40 people, with about 30 of those folks in research, development or engineering.
Q How is your bioinformatics unit organized within the framework of the organization? Is it part of the IT department, the biological research department, or some other department?
A I think we’re a bit non-traditional here because we’re a computationally driven discovery company. We have an engineering group that does the bulk of the IT and software development, but we also have an excellent technology development group that does algorithmic development and works very closely with the engineering group. We want the distinction between these groups to be rather fluid and people do move back and forth.
Q What non-existing technologies do you most wish you had? What’s lacking in the bioinformatics toolbox?
A The greatest thing about genomic biology is that there is almost always another way to look at a problem. If a computational approach doesn’t work, we can go to the bench to generate answers, or questions. What I wish we had more of was more information about the genomes of other species. I also wish we could quickly and cheaply determine all of the transcripts and proteins expressed in a single cell at any given time, non-invasively, of course, but that’s not on the horizon.