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The RAMEDIS system is a platform independent, web-based information system for rare metabolic diseases based on filed case reports. It was developed in close cooperation with clinical partners to allow them to collect information on rare metabolic diseases with extensive details, e.g. about occurring symptoms, laboratory findings, therapy and molecular data.
The Department of Energy Systems Biology Knowledgebase (KBase) is a software and data platform designed to meet the grand challenge of systems biology: predicting and designing biological function. KBase integrates data and tools in a unified graphical interface so users do not need to access them from numerous sources or learn multiple systems in order to create and run sophisticated systems biology workflows. Users can perform large-scale analyses and combine multiple lines of evidence to model plant and microbial physiology and community dynamics. KBase is the first large-scale bioinformatics system that enables users to upload their own data, analyze it (along with collaborator and public data), build increasingly realistic models, and share and publish their workflows and conclusions. KBase aims to provide a knowledgebase: an integrated environment where knowledge and insights are created and multiplied.
Rhea is a freely available and comprehensive resource of expert-curated biochemical reactions. It has been designed to provide a non-redundant set of chemical transformations for applications such as the functional annotation of enzymes, pathway inference and metabolic network reconstruction. There are three types of reaction participants (reactants and products): Small molecules, Rhea polymers, Generic compounds. All three types of reaction participants are linked to the ChEBI database (Chemical Entities of Biological Interest) which provides detailed information about structure, formula and charge. Rhea provides built-in validations that ensure both mass and charge balance of the reactions. We have populated the database with the reactions found in the enzyme classification (i.e. in the IntEnz and ENZYME databases), extending it with additional known reactions of biological interest. While the main focus of Rhea is enzyme-catalysed reactions, other biochemical reactions (including those that are often termed "spontaneous") also are included.
The MG-RAST server is an open source system for annotation and comparative analysis of metagenomes. Users can upload raw sequence data in fasta format; the sequences will be normalized and processed and summaries automatically generated. The server provides several methods to access the different data types, including phylogenetic and metabolic reconstructions, and the ability to compare the metabolism and annotations of one or more metagenomes and genomes. In addition, the server offers a comprehensive search capability. Access to the data is password protected, and all data generated by the automated pipeline is available for download in a variety of common formats. MG-RAST has become an unofficial repository for metagenomic data, providing a means to make your data public so that it is available for download and viewing of the analysis without registration, as well as a static link that you can use in publications. It also requires that you include experimental metadata about your sample when it is made public to increase the usefulness to the community.
>>>!!!<<< Sorry.we are no longer in operation >>>!!!<<< The Beta Cell Biology Consortium (BCBC) was a team science initiative that was established by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). It was initially funded in 2001 (RFA DK-01-014), and competitively continued both in 2005 (RFAs DK-01-17, DK-01-18) and in 2009 (RFA DK-09-011). Funding for the BCBC came to an end on August 1, 2015, and with it so did our ability to maintain active websites.!!! One of the many goals of the BCBC was to develop and maintain databases of useful research resources. A total of 813 different scientific resources were generated and submitted by BCBC investigators over the 14 years it existed. Information pertaining to 495 selected resources, judged to be the most scientifically-useful, has been converted into a static catalog, as shown below. In addition, the metadata for these 495 resources have been transferred to dkNET in the form of RDF descriptors, and all genomics data have been deposited to either ArrayExpress or GEO. Please direct questions or comments to the NIDDK Division of Diabetes, Endocrinology & Metabolic Diseases (DEM).