Today was the third and final day of the main ISMB conference! I slept in until noon (attending these things is surprisingly tiring) so I missed some of the morning sessions, but it was still a good day. Some highlights:
Workshop on alternative methods of peer review
The talks in this workshop focused on open access in publishing and scientific reproducibility. An increasingly popular topic is open peer review, where all aspects of the peer review process are published. This means the names of the reviewers, their comments and the author’s responses are all published with the online version of the article. In theory, this is a great idea. It increases openness, ensures readers are aware of problems with the article (both past and present) and lets authors know who is reviewing their article.
In practice, though, open peer review is difficult to implement. Some members of the audience brought up points of contention. For example, reviewers of a “big name” paper might be hesitant to criticize their superiors in the scientific community. Open peer review may also make it more difficult for editors to find reviewers for articles. The data say otherwise, though – since BMJ opened up the reveiw process, only 2% of editors have declined to review an article because of the change in policy. Other journals like F1000Research also operate on the open peer review model and seem to be doing just fine. I think the “openness” trend has just started to gain momentum and acceptance within the scientific community – it’ll be interesting to see how both authors and publishers respond in the future.
Final keynote by Russ Altman
The Altman lab at Stanford is doing some excellent work using informatics approaches to understand drug response. The ultimate goal is true pharmacogenetics and personalized medicine – imagine a doctor genotyping you in the office and picking a specific drug and dosage known to work best with your specific genes. His lab is doing a lot of machine learning and data mining on FDA drug interaction data and other publicly available sets. Along with some creative use of Amazon mechanical turk, they created a database of gene/drug relationships and ranked the side effects by severity.
The Altman lab is also working on predicting novel drug binding sites using protein structure. The method was complex and used a lot of interesting machine learning techniques (another reason I want all these talks to be online – going back to review and understand all the methods). In the end, they could predict small molecules most likely to interact with a protein’s active site and potentially inhibit it. These small molecules could be synthesized as part of a drug or found on another drug to re-purpose it.
The symposium then concluded with some closing remarks by the ISCB board members and awards for various posters and presentations. Overall, I was very pleased by the past few days and happy I attended. The personal and professional connections I made will help me in my search for a job and/or grad program. I saw some inspiring and interesting research, learned of cutting edge methods in the field and got to meet scientists I’ve only seen on paper before this week. A huge thanks to the ISCB members who organized this conference, as well as the Student Council for giving me the chance to present my research on Friday.