Event Abstract Back to Event The BrainGeneExpress Database: a data integration approach for neuroinformatic research oriented to systems biology Luciano Milanesi1*, Ettore Mosca1 and Roberta Alfieri1, 2 1 ITB-CNR, Italy 2 CILEA, Italy Computational neurobiology has a ancient history of successes in quantitative modelling and in the last few years a great number of quantitative experimental data have emerged. This represents the starting point to expand now the neuronal model in new directions, that is development of gene and protein interaction networks. The study of neurons, the brain and its development involves the knowledge of a large number of genes and molecular interactions and thus the systems biology approach is essential to describe the processes related to the pathology and to perform useful predictions. Starting from the integration of such data with experimental data it is possible to develop new discovery strategies in brain studies. For the effective application of the systemic approach it is essential to arrange information about genes, cellular pathways and interactions that they undertake. These annotations are publicly available in bioinformatics resources and their integration creates an added value allowing for example the clustering of brain-specific expressed genes by common signatures or the suggestion of possible annotations for genes not yet annotated. In this context we developed the BrainGeneExpress Database, a resource to support neuroinformatics research. The BrainGeneExpress DB contains up to date information regarding the mouse genes which have brain-specific gene expression patterns. The gene collection was built starting from the Mousebrain Gene Expression Map (BGEM) and the Allen Brain Atlas. We have capitalized on data integration to create an added value to the great amount of data available in the public repositories, for example using interactions information to suggest new possible annotations. Such annotations have been selected to point out the systemic approach and thus concern for example the pathway membership, physical and functional interactions and are all listed in the gene report. Therefore we have oriented the resource to systems biology due to the systemic properties of the considered disease and the great opportunities that such an approach can yield. Among the utilities, the infrastructure provides two tools for data mining: the first is based on molecular interactions data, while the second is an automated pipeline to find common annotations among genes. Starting from BioGRID dataset of interactions we have calculated all pairs shortest path using the Floyd€™s algorithm: examining shortest paths it is possible to elucidate unknown relations among genes and this could be the starting point for further studies. Moreover the neighbourhood information is used to suggest possible values for gene not yet annotated following the idea that there is a functional correlation among genes at a small distance in the network of interactions. Information on a given shortest path is integrated with gene reports and the search of common annotations, thus helping to elucidate new relationship among genes and to draw wiring diagrams. Conference: Neuroinformatics 2008, Stockholm, Sweden, 7 Sep - 9 Sep, 2008. Presentation Type: Poster Presentation Topic: Genomics and Genetics Citation: Milanesi L, Mosca E and Alfieri R (2008). The BrainGeneExpress Database: a data integration approach for neuroinformatic research oriented to systems biology. Front. Neuroinform. Conference Abstract: Neuroinformatics 2008. doi: 10.3389/conf.neuro.11.2008.01.077 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 28 Jul 2008; Published Online: 28 Jul 2008. * Correspondence: Luciano Milanesi, ITB-CNR, Segrate, Italy, luciano.milanesi@itb.cnr.it Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Luciano Milanesi Ettore Mosca Roberta Alfieri Google Luciano Milanesi Ettore Mosca Roberta Alfieri Google Scholar Luciano Milanesi Ettore Mosca Roberta Alfieri PubMed Luciano Milanesi Ettore Mosca Roberta Alfieri Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.