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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.
MassIVE is a community resource developed by the NIH-funded Center for Computational Mass Spectrometry to promote the global, free exchange of mass spectrometry data. MassIVE datasets can be assigned ProteomeXchange accessions to satisfy publication requirements.
<<<!!!<<< Retirement of UniProt Metagenomic and Environmental Sequences (UniMES): UniProt has retired UniMES as there is now a resource at the EBI that is dedicated to serving metagenomic researchers. Henceforth, we recommend using the EBI Metagenomics portal instead https://www.ebi.ac.uk/metagenomics/ . In addition to providing a repository of metagenomics sequence data, EBI Metagenomics allows you to view functional and taxonomic analyses and to submit your own samples for analysis. >>>!!!>>> The UniProt Metagenomic and Environmental Sequences (UniMES) database is a repository specifically developed for metagenomic and environmental data. We provide UniMES clusters in order to obtain complete coverage of sequence space at different resolutions.