BBSRC Systems Biology Grantholder Workshop, University of Nottingham, 16 December 2008.
I really enjoyed this workshop – met new people, chatted about systems biology, clinical genetics, surname-DNA associations, The Princess Bride and Spinal Tap. From a combination of presentations and chats, two defining topics of discussion in this workshop emerged:
- social challenges, or getting the different disciplines within systems biology to understand one another. Alternatively, people also mentioned the challenge in getting different collaborating groups to work together;
- stable infrastructure funding, or getting money for supporting software and for building and supporting data standards.
In my opinion, the former is much less of a current challenge than the latter. From my personal experiences within CISBAN (which contains a variety of experimental biologists as well as different types of theoretical biologists, mathematicians and statisticians), we have progressed to the point that I really feel that each "group" understands what the others do. In other words, in a local context, I think that social challenges are minimal. Longer-distance social challenges will remain around a little longer, but with the increasing use of online social networking tools (1, 2, 3, 4, 5, 6), I think much of this could be minimized. In contrast, I think that the challenges in getting funding for stable infrastructure (software and data standards) isn't advancing as quickly as it should. The production and maintenance of life-science data standards are vital to more efficient data sharing and collaboration. People should make room in their grants for the development of data standards (e.g. MIBBI guidelines, syntaxes or semantics – see Frank's excellent discussion on the issue) that will benefit them. Core institutes such as the EBI do a lot of this work, but can't get funding for everything.
I started thinking about all this stuff on Wednesday morning, and writing this did somewhat affect the notes I took in some of the talks, and for that I apologise! 🙂
And, in conclusion, some light entertainment. There was a third category of discussion which many will be familiar with:
I'm as guilty as the rest of them. Here's a small selection of examples of how much us scientists love our acronyms, and those things which are very close to true acronyms: APPLE, BASIS, CRISP, EMMAS, PRESTA, PheroSys, Phyre, PiMS, SToMP, SyMBA (mine), SysMO, SUMO, ROBuST and others. For a guide to how to build acronyms, see the PhD Comic's excellent summary of the topic (and the related FriendFeed discussion).