Neuroinformatics 2009

2009-09-10

This is the third year in a row that I have been to Neuroinformatics (or it's forerunner, Databasing the Brain). It's still turning out to be an enjoyable meeting, even though there is still lots of it that I don't understand. Come to think of, perhaps because there is lots of it that I don't understand.

Pilsen (or Plzen) is, perhaps, a strange place for the meeting. It's a bit of a pig to get to, as the airport is in Prague. Likewise, the conference centre was a bit out of town, so you had to get a taxi if you wanted food in the evening. Still the venue itself worked well. Slightly flaky wireless, but it had tables upstairs on a balcony; a lot of people migrated up there as the meeting went on, making the auditorium a little deserted.

Although, I've said I didn't understand lots of it, many of the keynotes this year were bioinformatics, systems biology or data integration which I know well. As well as that, there was a (semantic) web and ontology section. I enjoyed Tim Clarks talk, as he's made stuff that lots of people are actually using, although I don't think he explained why during his talk.

The section of high performance computing was probably the least relevant. While they've become interested in power consumption recently, these guys are still obsessed with teraflops (...​now petaflops...​now exaflops). To be honest, I don't care. With more power, you can build more granular, higher resolution models, but I doubt that will bring you anything, unless you also have more granular data. They should be worried about discs --- always the Cindarella of the hardware world, only slightly more interesting than printers --- but it's discs which carry the data. While we are at it, spinning discs use lots of power. And they have more flashing lights than CPUs. The hardware guys should be talking about disc space. The neuroscientists should be worrying about filling discs up. Neuroinformaticians should make that they end up with an exabyte dataset; not 1000 petabyte datasets or worse, 1,000,000 gigabyte datasets.

I tried to get a bit of Web 2.0 stuff happening at the meeting. David Sutherland set up a friendfeed room. Second day, we were sitting next to each other like two sad blokes at a party full of women, sending each other messages on their iphones. Although, it was a neuroinformatics meeting, so largely without the women. Second day, mostly it was just me, sad, lonely and pathetic. Still, having said that, I did manage to meet almost all of those subscribed to the room, which you couldn't achieve at ISMB nowadays. Pavan Ramkumar said hello at lunch, and then later at the airport. I met Sarah Maynard at her poster; it had ontologies, OWL and information content-based similarity measures; bound to make me happy. Only Lisa Kjonigsen remained in cyberspace only. With luck, next year, more people will join; not least because I'll probably not go to Japan.

I had a quick go at live blogging also; to be honest, I am not a natural. The problem is I have too much desire to editorialise. The roboblogger tells me that she just blogs the notes that she would have taken anyway; my notes, on the other hand, are full of comment, invective and questions. Perhaps I could just put these into the asciidoc source of my blog as comments. I stopped live blogging on the last day, not for these reasons, but largely as a desire not to hold my crushing ignorance of the topics being discussed up to public scrutiny.

Neuroinformatics (the meeting) is changing. I have to believe that if there is more about genomic and multiomic data integration that this has to be a good thing. The brain is a hard to thing to figure out; I have to believe that using more data, more types of data and a heavier use of nice, simple, model organisms is going to increase the rate of advance; with all the fuss about systems biology, it's easy to forget the fabulous success of the last 100 years of reductionism biology, which made systems biology possible. This has to be the way forward for neuroscience. Even if it does make the meeting more usual and, perhaps, less interesting for me as a result.