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The Maize Genetics and Genomics Database focuses on collecting data related to the crop plant and model organism Zea mays. The project's goals are to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models. MaizeGDB also aims to make the Maize Newsletter available, and provide support services to the community of maize researchers. MaizeGDB is working with the Schnable lab, the Panzea project, The Genome Reference Consortium, and iPlant Collaborative to create a plan for archiving, dessiminating, visualizing, and analyzing diversity data. MMaizeGDB is short for Maize Genetics/Genomics Database. It is a USDA/ARS funded project to integrate the data found in MaizeDB and ZmDB into a single schema, develop an effective interface to access this data, and develop additional tools to make data analysis easier. Our goal in the long term is a true next-generation online maize database.aize genetics and genomics database.
GeneWeaver combines cross-species data and gene entity integration, scalable hierarchical analysis of user data with a community-built and curated data archive of gene sets and gene networks, and tools for data driven comparison of user-defined biological, behavioral and disease concepts. Gene Weaver allows users to integrate gene sets across species, tissue and experimental platform. It differs from conventional gene set over-representation analysis tools in that it allows users to evaluate intersections among all combinations of a collection of gene sets, including, but not limited to annotations to controlled vocabularies. There are numerous applications of this approach. Sets can be stored, shared and compared privately, among user defined groups of investigators, and across all users.
KiMoSys, a web application for quantitative KInetic MOdels of biological SYStems. Kinetic models, with the aim to understand and subsequently design the metabolism of organism of interest are constructed iteratively and require accurate experimental data for both the generation and verification of hypotheses. Therefore, there is a growing requirement for exchanging experimental data and models between the systems biology community, and to automate as much as possible the kinetic model building, editing, simulation and analysis steps.
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Arachne is the central object-database of the German Archaeological Institute (DAI). In 2004 the DAI and the Research Archive for Ancient Sculpture at the University of Cologne (FA) joined the effort to support Arachne as a tool for free internet-based research. Arachne's database design uses a model that builds on one of the most basic assumptions one can make about archaeology, classical archaeology or art history: all activities in these areas can most generally be described as contextualizing objects. Arachne tries to avoid the basic mistakes of earlier databases, which limited their object modeling to specific project-oriented aspects, thus creating separated containers of only a small number of objects. All objects inside Arachne share a general part of their object model, to which a more class-specific part is added that describes the specialised properties of a category of material like architecture or topography. Seen on the level of the general part, a powerful pool of material can be used for general information retrieval, whereas on the level of categories and properties, very specific structures can be displayed.