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Found 34 result(s)
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.
METLIN represents the largest MS/MS collection of data with the database generated at multiple collision energies and in positive and negative ionization modes. The data is generated on multiple instrument types including SCIEX, Agilent, Bruker and Waters QTOF mass spectrometers.
Reactome is a manually curated, peer-reviewed pathway database, annotated by expert biologists and cross-referenced to bioinformatics databases. Its aim is to share information in the visual representations of biological pathways in a computationally accessible format. Pathway annotations are authored by expert biologists, in collaboration with Reactome editorial staff and cross-referenced to many bioinformatics databases. These include NCBI Gene, Ensembl and UniProt databases, the UCSC and HapMap Genome Browsers, the KEGG Compound and ChEBI small molecule databases, PubMed, and Gene Ontology.
Gramene is a platform for comparative genomic analysis of agriculturally important grasses, including maize, rice, sorghum, wheat and barley. Relationships between cereals are queried and displayed using controlled vocabularies (Gene, Plant, Trait, Environment, and Gramene Taxonomy) and web-based displays, including the Genes and Quantitative Trait Loci (QTL) modules.
EnsemblPlants is a genome-centric portal for plant species. Ensembl Plants is developed in coordination with other plant genomics and bioinformatics groups via the EBI's role in the transPLANT consortium.
CorrDB has data of cattle, relating to meat production, milk production, growth, health, and others. This database is designed to collect all published livestock genetic/phenotypic trait correlation data, aimed at facilitating genetic network analysis or systems biology studies.
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iDog, an integrated resource for domestic dog (Canis lupus familiaris) and wild canids, provides the worldwide dog research community a variety of data services. This includes Genes, Genomes, SNPs, Breed/Disease Traits, Gene Expressions, Single Cell, Dog-Human Homolog Diseases and Literatures. In addition, iDog provides Online tools for performing genomic data visualization and analyses.
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Morph·D·Base has been developed to serve scientific research and education. It provides a platform for storing the detailed documentation of all material, methods, procedures, and concepts applied, together with the specific parameters, values, techniques, and instruments used during morphological data production. In other words, it's purpose is to provide a publicly available resource for recording and documenting morphological metadata. Moreover, it is also a repository for different types of media files that can be uploaded in order to serve as support and empirical substantiation of the results of morphological investigations. Our long-term perspective with Morph·D·Base is to provide an instrument that will enable a highly formalized and standardized way of generating morphological descriptions using a morphological ontology that will be based on the web ontology language (OWL - http://www.w3.org/TR/owl-features/). This, however, represents a project that is still in development.
The database aims to bridge the gap between agent repositories and studies documenting the effect of antimicrobial combination therapies. Most notably, our primary aim is to compile data on the combination of antimicrobial agents, namely natural products such as AMP. To meet this purpose, we have developed a data curation workflow that combines text mining, manual expert curation and graph analysis and supports the reconstruction of AMP-Drug combinations.
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.
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.
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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.
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The project brings together national key players providing environmentally related biological data and services to develop the ‘German Federation for Biological Data' (GFBio). The overall goal is to provide a sustainable, service oriented, national data infrastructure facilitating data sharing and stimulating data intensive science in the fields of biological and environmental research.
The Yeast Resource Center Public Image Repository is a database of fluorescent microscopy images and their associated metadata/experimental parameters. The images depict the localization, co-localization and FRET (fluorescence energy transfer) of proteins in cells, particularly in the budding yeast Saccharomyces cerevisiae as a model organism. Users may download the entire datasets to improve their research.
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BACTIBASE contains calculated or predicted physicochemical properties of bacteriocins produced by both Gram-positive and Gram-negative bacteria. The information in this database is very easy to extract and allows rapid prediction of relationships structure/function and target organisms of these peptides and therefore better exploitation of their biological activity in both the medical and food sectors.
This site provides access to complete, annotated genomes from bacteria and archaea (present in the European Nucleotide Archive) through the Ensembl graphical user interface (genome browser). Ensembl Bacteria contains genomes from annotated INSDC records that are loaded into Ensembl multi-species databases, using the INSDC annotation import pipeline.
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.
The Human Ageing Genomic Resources (HAGR) is a collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses.
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Cotton Functional Genomics Database (CottonFGD) integrates with modern genomic/transcriptomic data and earch/analysis/visualization modules. It aims at providing an easy, quick and visualized data analysis platform for cotton (Gossypium spp) researchers and other functional genomic researches.