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!