An Exercise in Irrelevance

This is a live blog from Neuroinformatics 2009.

Neuron systems are incredible stable over time. Looking at a number of systems, including pyloric pattern generator — stomachs in crabs (?). Is a pacemaker system; it’s very stable between individuals and over time. Despite this, for example, the maximal conductance in the neurons varies pretty widely. How come this variability doesn’t affect stability?

Have generator a single compartment model, looking at 8 dimensional parameter space and making a big database. Trying to replicate the variance that they see within the biological systems. Tend, with their model, to get similar output for these different conditions. Conclusion of this is that neuronal system have a large solution space within which they maintain their functioning.

Question, how are these solution spaces distributed within the total parameter space? Could be a single unique solution, could be islands, etc. Been collaborating in high-dimensional space visualisation using dimensional stacking. Think it’s a slices through the dimensional space, stacked out side-by-side.

Talks about cell-type specific co-regulation of ion channels; there are lots of correlations between different forms of current. Interestingly, most of the relationships are linear and, so far, all of them are positive; it’s not clear that there are any negative correlations.

Have classified their model space. Found that correlation between channels is always in the same direction — a correlation which is positive in one cell type will never be negative in another. However, they are showing a negative relationship in some circumstances, when the experimental processes show a positive relationship which is an open question.

This talk was given as a keynote at Neuroinformatics 2009.

This is my first attempt at live blogging a conference talk, so please read it in this light.

There is an overlap between neuroinformatics and bioinformatics; one example of this is the necessity for data integration between the two. Looking to the future; suggests that every database will have a canonical atlas; high-throughout measurements; dynamic live-brain imaging and mesoscopic biology; relationship to disese and pathology.

First step was taken by Allen brain atlas, to expression of genes to atlas to be of any use. Altas is now linked out to pretty much everything else; mostly through genes and gene IDs.

Example of systems biology approach to prion disease — injected prion into a variety of different mouse backgrounds. Looked for changes in expression in many different genes. Are a number of factors affecting prion disease; distinct prion strains cause different effects in the same background.

Highlights the necessity for standards in mass spectrometry if you wish to make quantative comparisions. More generally, this allows integration from many different data types, producing extension descriptions, for example, of a macrophage response.

Building a big integrated database of lipid metabolism.

Looked at oxidative stress in endothelial cells; again, did this by integrating knowledge from many different forms of experiment.

Next gen sequencing, ChIPing and digital gene expression. ChIP is massive sequencing of immunopreciptated chromatin DNA. Requries no PCR, so no amplification bias which is a problem for repetitive DNA.

Molecular imaging in vitro and in vivo; again gives a set of examples of where this is being used in xenopus and human; suggests relating fMRI data to genomic and other data will be the next big challenge.

Molecular modelling is also useful for integrating data. Gives set of example,s including calcium control within the cell. Were able to reproduce Calcium profile of many different gene knockouts and knockdowns from this sort of model.

One of the questins was:

How much data can you share — answer, all of it, with metadata if you want it to be useful!

I’ve just arrived at the conference centre in Pilsen for Neuroinformatics 2009. I got into Pilsen last night, exhausted from the flights and lack of sleep, especially after Science Online. Ironically, I was so knackered last night, that I was in the bedroom by 10 which, follow the traditional hour of fiddling with the aircon to get a reasonable temperature, meant I still got a good nights sleep and managed to get up early. To the point that my phone alarm annouced “It’s time to get up”, loudly in the taxi here.

Pilsen (or Plzen) is famous as being home to the lager. If you didn’t know this before you got here, you will after. I’m staying in the Hotel Angelo, which is near the middle of town and right opposite the brewery. Last night, was Pilsfest — yep, land in Czech and there is a beer festival on; either I must be lucky, or they have a lot of beer festivals. We drove here from the Prague; the countryside is green and beautiful, with magnificient, dark green decidious trees everywhere. Pilsen is built around a central square with a church; there’s the odd motif about the place with makes it foreign to me; the odd tower that looks like a minaret; the ornamentation under the eves of the building and the strange psch, psch, psch of the language.

Weather is cool, and autumnal just like Newcastle (well, maybe a wee bit warmer). Just after I arrived, while I was wandering around the beer festival, the skys opened and it rained torrentially. Fortunately, it was over quickly, and we ended up going to the inevitable Italian resturant — has a pizza, wasn’t great.

I have a decision to make; the last few conferences I’ve been to, the roboblogger was there, knocking out live blogs; I think that these are useful but, generally, can’t be bothered to do them myself. But in the absence of 100 keen bloggers, perhaps I should have a go this time.