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Found 9 result(s)

DisProt

Database of Protein Disorder

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The Database of Protein Disorder (DisProt) is a curated database that provides information about proteins that lack fixed 3D structure in their putatively native states, either in their entirety or in part. DisProt is a community resource annotating protein sequences for intrinsically disorder regions from the literature. It classifies intrinsic disorder based on experimental methods and three ontologies for molecular function, transition and binding partner.

Rhea

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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.

SWISS-MODEL Repository

SMR

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The SWISS-MODEL Repository is a database of annotated three-dimensional comparative protein structure models generated by the fully automated homology-modelling pipeline SWISS-MODEL.

MassBank Europe

MassBank

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Database of mass spectra of known, unknown and provisionally identified substances. MassBank is the first public repository of mass spectral data for sharing them among scientific research community. MassBank data are useful for the chemical identification and structure elucidation of chemical compounds detected by mass spectrometry.

UniProtKB

UniProtKnowledgebase

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The UniProt Knowledgebase (UniProtKB) is the central hub for the collection of functional information on proteins, with accurate, consistent and rich annotation. In addition to capturing the core data mandatory for each UniProtKB entry (mainly, the amino acid sequence, protein name or description, taxonomic data and citation information), as much annotation information as possible is added. This includes widely accepted biological ontologies, classifications and cross-references, and clear indications of the quality of annotation in the form of evidence attribution of experimental and computational data. The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), and the UniProt Archive (UniParc). The UniProt Metagenomic and Environmental Sequences (UniMES) database is a repository specifically developed for metagenomic and environmental data. The UniProt Knowledgebase,is an expertly and richly curated protein database, consisting of two sections called UniProtKB/Swiss-Prot and UniProtKB/TrEMBL.

Emage

e-Mouse Atlas of Gene Expression

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EMAGE (e-Mouse Atlas of Gene Expression) is an online biological database of gene expression data in the developing mouse (Mus musculus) embryo. The data held in EMAGE is spatially annotated to a framework of 3D mouse embryo models produced by EMAP (e-Mouse Atlas Project). These spatial annotations allow users to query EMAGE by spatial pattern as well as by gene name, anatomy term or Gene Ontology (GO) term. EMAGE is a freely available web-based resource funded by the Medical Research Council (UK) and based at the MRC Human Genetics Unit in the Institute of Genetics and Molecular Medicine, Edinburgh, UK.

GENCODE

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GENCODE is a scientific project in genome research and part of the ENCODE (ENCyclopedia Of DNA Elements) scale-up project. The GENCODE consortium was initially formed as part of the pilot phase of the ENCODE project to identify and map all protein-coding genes within the ENCODE regions (approx. 1% of Human genome). Given the initial success of the project, GENCODE now aims to build an “Encyclopedia of genes and genes variants” by identifying all gene features in the human and mouse genome using a combination of computational analysis, manual annotation, and experimental validation, and annotating all evidence-based gene features in the entire human genome at a high accuracy.

MG-RAST

Metagenomics analysis server

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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.

Gene Ontology

GO

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The mission of the GO Consortium is to develop a comprehensive, computational model of biological systems, ranging from the molecular to the organism level, across the multiplicity of species in the tree of life. The Gene Ontology (GO) knowledgebase is the world’s largest source of information on the functions of genes. This knowledge is both human-readable and machine-readable, and is a foundation for computational analysis of large-scale molecular biology and genetics experiments in biomedical research.