Director of the Computational Medicine Center at Thomas Jefferson University in Philadelphia, PA, and alumnus of the Courant Institute of Mathematical Studies, Computational Biologist Isidore Rigoutsos recently shared his thoughts on a current situation he finds both fascinating and confounding: the two contrasting ways of thinking concerning, on the one hand, historically-accepted bodies of knowledge, and on the other, today’s overwhelming abundance of data.
“In April 2010, there were two one-page articles in the journal Nature that are very representative of the two schools of thought that exist in biology and medicine right now,” he notes. “The first takes the traditional approach where someone understands a domain intimately well, such as a gene or disease. This person thinks hard and long and comes up with a hypothesis, then says, ‘Let’s do a test in the lab.’ This is how we practiced science for quite a few years.”
The second approach, he says, is the result of advances in computational sciences and technology. “We now have the ability to generate tons of data in a guided way from a cell, a tissue, or an organism. So the question is, can we figure out what the data is telling us? How can we exploit this unprecedented capability to answer existing questions, as well as break new ground and advance knowledge?”
In the first approach, Rigoutsos explains, the scientist is limited by his or her imagination. In the second, one is limited by technology, and technology has been making great strides. “This is where it gets interesting,” he says, “because we can now generate information about individual cells that we could not have fathomed ten years ago. It challenges you to think in ways you wouldn’t have done if you followed what the books say.”
Commonly, in situations where data says one thing and the books say another, Rigoutsos and his colleagues are faced with a choice: Which one to believe? “My position has always been, believe the data,” he states firmly. “It doesn’t matter what your personal beliefs are, it doesn’t matter what the books say. If the result is repeatable and the experiment has been done correctly, you have to believe the data. You have to learn to liberate yourself from the constraints that come with formal education. As scientists, we are trained to think differently but when it comes to practicing it, it’s not always easy,” he says.
According to Dr. Rigoutsos, there is an increasing realization by the medical community that the new way of doing science, namely, smart processing of big data, will shape our scientific activities for years to come. This, he says, will likely be a long process but will happen. “You need to train new people while also convincing the practitioners who have been doing it a different way that they have more to gain if they open themselves to this new possibility,” he states. “Biology and information science took about 20 years to converge, so we’re probably looking at 20 years if not more for medicine, with the end result that medicine will be practiced in a radically different way.”
By M.L. Ball