INIA: Informatics Core

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DESCRIPTION (provided by applicant): The Informatics Core of the Integrative Neurosciences Initiative on Alcoholism (INIA) provides central informational and computational resources for the different INIA research projects and cores. This INIA informatics core will, first, provide the collaborative information management, information technologies, and databases that are critical for these INIA projects to acquire and manage their data. The informatics core will develop a number of collaborative information systems that should help break down the geographic barriers to scientific collaboration; this core will enable the evaluation and direct application of these information-technology-backed collaborative tools for use by MA researchers. For exploratory research, several electronic laboratory notebooks will be developed. In addition, web-accessible lab information systems will also be built for larger-scale data discovery projects that allow central tracking and sharing of very different kinds of phenotype data about the same mouse strain from different research labs and institutions. Secondly, this core will provide some computational analysis and data mining tools that should enable INIA researchers to sift through their data for interesting patterns, especially patterns that might suggest hypotheses that can be tested by further experiments. In addition, the core will help initiate and foster collaborations between experimental INIA researchers and other computational researchers that might not be directly funded by this project. Thirdly, this core needs to make the finished INIA information freely available to the entire community via database-backed web sites and promote interperability of its data with data from other projects. For the subset of data that a community database can accept, the informatics core will need to package and forward that data to them. This core will work with other informatics researchers and developers on common data schemas, domain ontologies, data formats, and other ways to promote interperability across different data and databases.