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The Ensembl project produces genome databases for vertebrates and other eukaryotic species. Ensembl is a joint project between the European Bioinformatics Institute (EBI) and the Wellcome Trust Sanger Institute (WTSI) to develop a software system that produces and maintains automatic annotation on selected genomes.The Ensembl project was started in 1999, some years before the draft human genome was completed. Even at that early stage it was clear that manual annotation of 3 billion base pairs of sequence would not be able to offer researchers timely access to the latest data. The goal of Ensembl was therefore to automatically annotate the genome, integrate this annotation with other available biological data and make all this publicly available via the web. Since the website's launch in July 2000, many more genomes have been added to Ensembl and the range of available data has also expanded to include comparative genomics, variation and regulatory data. Ensembl is a joint project between European Bioinformatics Institute (EBI), an outstation of the European Molecular Biology Laboratory (EMBL), and the Wellcome Trust Sanger Institute (WTSI). Both institutes are located on the Wellcome Trust Genome Campus in Hinxton, south of the city of Cambridge, United Kingdom.
This Animal Quantitative Trait Loci (QTL) database (Animal QTLdb) is designed to house all publicly available QTL and trait mapping data (i.e. trait and genome location association data; collectively called "QTL data" on this site) on livestock animal species for easily locating and making comparisons within and between species. New database tools are continuely added to align the QTL and association data to other types of genome information, such as annotated genes, RH / SNP markers, and human genome maps. Besides the QTL data from species listed below, the QTLdb is open to house QTL/association date from other animal species where feasible. Note that the JAS along with other journals, now require that new QTL/association data be entered into a QTL database as part of their publication requirements.
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CAZy is a specialist database dedicated to the display and analysis of genomic, structural and biochemical information on Carbohydrate-Active Enzymes (CAZymes). CAZy data are accessible either by browsing sequence-based families or by browsing the content of genomes in carbohydrate-active enzymes. New genomes are added regularly shortly after they appear in the daily releases of GenBank. New families are created based on published evidence for the activity of at least one member of the family and all families are regularly updated, both in content and in description.
SwissLipids is an expert curated resource that provides a framework for the integration of lipid and lipidomic data with biological knowledge and models.
The Comparative RNA Web (CRW) Site disseminates information about RNA structure and evolution that has been determined using comparative sequence analysis. We present both raw (sequences, structure models, metadata) and processed (analyses, evolution, accuracy) data, organized into four main sections.
TAED is a database of phylogenetically indexed gene families. It contains multiple sequence alignments from MAFFT1, maximum likelihood phylogenetic trees from PhyML2, bootstrap values for each node, dN/dS ratios for each lineage from the free ratios model in PAML3, and labels for each node of speciation or duplication from gene tree/species tree reconciliation using SoftParsMap4. The phylogenetic indexing enables simultaneous viewing of lineages with high dN/dS that occurred along the same species tree branches. Resources from the Protein Data Bank (PDB) and the Kyoto Encyclopedia of Genes and Genomes (KEGG)5, have been incorporated into the TAED analysis to detect substitutions along each branch within the phylogenetic tree and to assess selection within pathways.
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.