The Pulse of Computational Biology at #CBSymp16
The @PLOSCompBiol symposium #CBSymp16, held last Friday at the @NIH, saw the progenitors and practitioners of computational biology deliberate how this relatively new scientific field now stands on firm grounds. Computational biology is fast becoming an independent and integral part of the modern biological sciences, and the excitement for its rapid growth was in the air!
But this was not always clear, reminisced Philip E. Bourne (@pebourne), Associate Director for Data Science at NIH and the founding Editor-in-Chief of the PLoS Computational Biology journal. Starting the proceedings for the day, he said the open-access journal was created in 2005 within the PLOS family after being passed in committee by one vote and it took the tireless work of a small team to keep everything on track.
“‘Open access’, ‘open science’… in 2005 it was a bit confusing what all that meant. Now it’s gained a great deal of momentum.” — Philip E. Bourne
Jason Papin (@papinsysbio), Professor at the University of Virginia and current co-Editor-in-Chief of PLoSCompBiol, used the number of page edits to the Wikipedia article on ‘Computational Biology’ to showcase how broad and specialized the field has become, a journey that snugly coincides with the growth of the journal itself.
Endorsing this growth and diversification, Kim ‘Avrama’ Blackwell, Professor at the George Mason University, said that we know computational biology has become such an important part of biological research when, often, the ‘computation’ is almost invisible, getting subsumed into the experimental techniques of a sub-field. A similar sentiment has been shared by the likes of Gates and Jobs about sufficiently advanced technology just disappearing into the core function.
A sign of development of the field is also the readiness of its community to grapple with complex issues and to take stock of critical challenges. The various talks and panels of the symposium rang true to this initiative, bringing several issues revolving around ‘open science’, ‘open access’, ‘reproducibility’, ‘community standards’, and ‘publishing negative results’ to the forefront. Through the ensuing discussion, everyone could agree that much of the solution to these issues lies in continued community-wide efforts towards improving interactions with experimentalists/clinicians and enhancing computational education across the board.
“There’s going to be a complete inversion of the traditional education to genomics and computing” — Mark Gerstein
Addressing the latter, Mark Gerstein (@markgerstein), Professor at Yale University, argued that the future holds a new kind of education to genomics and computing. Moderating a panel discussion on “How Computational Biology and Computing in General Will Affect Human Health”, he remarked that the past and predominant current trend is to begin with learning molecular/cellular biology, then get interested in genomics, and then get introduced to computational methods for approaching these problems. In the future, he predicted, everyone’s introduction to genomics will be through their personal genome, molecular biology coming later on to functionally interpret mutations, with computational biology bridging the gap.
As a student of this field over time, I have preferred being called a ‘computational biologist’ — instead of, say, ‘bioinformatician’ — as I see myself as a true biologist interested in answering fascinating questions in biology and whose approach happens to be computational/quantitative. Now, as an aspiring early-career researcher, at the symposium, I was immensely glad to see this spirit shared widely; to see that the field of computational biology is well-recognized for its significant current and future impact on biology and medicine.
Arjun Krishnan is currently a senior researcher at Princeton University and soon to be an Asst. Professor at Michigan State University | www.arjun-krishnan.net | @compbiologist
Any views expressed in the blog post are his own and not necessarily those of PLoS.
