Neuroinformatics is the second step in the Blue Brain workflow. The goal is to extract the maximal possible information from data acquisition in the previous step. To achieve this goal, the project has designed a set of prototype workflows supporting the acquisition, curation, databasing, post-processing and mining of data (protocols, experimental conditions, results) from Blue Brain experiments and from the literature.
One of the project’s key strategies is to exploit interdependencies in the experimental data to build comprehensive digital reconstructions of the brain, including features that have yet to be characterized experimentally. The BBP has applied this strategy in several different areas (prediction of the spatial distribution of ion channels in 3D model neurons, prediction of neuronal firing properties from expression data for a selected set of ion channels, prediction of synaptic con¬nectivity from neuronal morphology). In future work, the project plans to extend its use to new domains, including the prediction of structural and functional features of the human, from sparse human data augmented with data collected in rodents.