And Sydney Brenner, of course, was always open to it. And I think was in favor of it from the beginning. Actually, he was one of the first people—I was working in mathematics and computation for most of my career and most of the biomedical scientists were ill at ease with that, with computation and mathematics. And a lot of them didn’t see it addressing and they were right. A lot of them didn’t see it addressing the problems that most biologists were interested in. And a lot of them were ill at ease with it. Sydney Brenner was one of the first major biologists who I heard say something like, it’s not a ridiculous idea to think of training a computer to begin to recognize functional regions on DNA. He said that at a meeting in 1986 in Germany. I felt so good when—because I had been working on this a few years earlier and we made some progress on that problem. And I thought that no biologist is going to take this seriously. And to hear him say that actually made me think, well, boy, there’s some really smart people around. And it may not be such a crazy thing to think about these things. To think that they are going to happen because there was no doubt that if we started developing sequences the way the genome project proposed to do, there was no doubt that computers were not just going to serve as a filing cabinet, basically for storing and manipulating and retrieving data, but were going to serve as a method to analyze the data to begin to form hypotheses so that early on experimentalists knew where to look at one thousand different possible places to look.

You know, how do you place your priorities? There was no doubt that computational method, the type of ________pattern recognition algorithms we have now, the computer learning algorithms. They all had to come into play. And they have. In fact, one of the other really major sociological phenomena—one of the real changes is the response of the computer science community to genomics. I mean that is a shift that had to happen and if happened with tremendous dexterity. That is to say, that the computer science departments around the nation and some of the real leaders got involved in genomics, and without their involvement we would have had a much, much more difficult time in this. And it affects every aspect of computer science, genomics.

So that’s a sociological, that’s something I think that the sociologists of science will be studying for some time.

Charles DeLisi did pioneering work in theoretical and mathematical immunology. He received his Ph.D. in physics and did postdoctoral studies in the chemistry department at Yale University researching RNA structure. He became a theoretical physicist at Los Alamos National Laboratory and then moved to the National Institute of Health, where he worked on molecular and cell immunology for ten years.

DeLisi is currently director of the Biomolecular Systems Laboratory, Chair of the Bioinformatics Program, Metcalf Professor of Science and Engineering and Dean Emeritus of the College of Engineering at Boston University.

Charles DeLisi develops computational methods for high throughput genomic and proteomic analysis. His laboratory is helping to develop technologies for fingerprinting the complete molecular state of a cell. He is interested in finding computational methods for determining protein function and researches the structural basis of signal translation by membrane bound receptors, the structural basis of voltage gating, and the docking of peptide hormones and neurotransmitters at their sites of action.

In 1986, DeLisi and Watson met at a CSHL meeting and spoke about their interests in sequencing the human genome.