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Found 64 result(s)
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The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), advances life & health sciences by providing open access to a suite of resources, with the aim to translate big data into big discoveries and support worldwide activities in both academia and industry.
The ProteomeXchange consortium has been set up to provide a single point of submission of MS proteomics data to the main existing proteomics repositories, and to encourage the data exchange between them for optimal data dissemination. Current members accepting submissions are: The PRIDE PRoteomics IDEntifications database at the European Bioinformatics Institute focusing mainly on shotgun mass spectrometry proteomics data PeptideAtlas/PASSEL focusing on SRM/MRM datasets.
The European Nucleotide Archive (ENA) captures and presents information relating to experimental workflows that are based around nucleotide sequencing. A typical workflow includes the isolation and preparation of material for sequencing, a run of a sequencing machine in which sequencing data are produced and a subsequent bioinformatic analysis pipeline. ENA records this information in a data model that covers input information (sample, experimental setup, machine configuration), output machine data (sequence traces, reads and quality scores) and interpreted information (assembly, mapping, functional annotation). Data arrive at ENA from a variety of sources. These include submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centres and routine and comprehensive exchange with our partners in the International Nucleotide Sequence Database Collaboration (INSDC). Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and to provide optimal submission systems and data access tools that work seamlessly with the published literature.
<<<!!!<<< Efforts to obtain renewed funding after 2008 were unfortunately not successful. PANDIT has therefore been frozen since November 2008, and its data are not updated since September 2005 when version 17.0 was released (corresponding to Pfam 17.0). The existing data and website remain available from these pages, and should remain stable and, we hope, useful. >>>!!!>>> PANDIT is a collection of multiple sequence alignments and phylogenetic trees. It contains corresponding amino acid and nucleotide sequence alignments, with trees inferred from each alignment. PANDIT is based on the Pfam database (Protein families database of alignments and HMMs), and includes the seed amino acid alignments of most families in the Pfam-A database. DNA sequences for as many members of each family as possible are extracted from the EMBL Nucleotide Sequence Database and aligned according to the amino acid alignment. PANDIT also contains a further copy of the amino acid alignments, restricted to the sequences for which DNA sequences were found.
<<<!!!<<< This site is no longer maintained and is provided for reference only. Some functionality or links may not work. For all enquiries please contact the Ensembl Helpdesk http://www.ensembl.org/Help/Contact >>>!!!>>> PhytoPath is a new bioinformatics resource that integrates genome-scale data from important plant pathogen species with literature-curated information about the phenotypes of host infection. Using the Ensembl Genomes browser, it provides access to complete genome assembly and gene models of priority crop and model-fungal, oomycete and bacterial phytopathogens. PhytoPath also links genes to disease progression using data from the curated PHI-base resource. PhytoPath portal is a joint project bringing together Ensembl Genomes with PHI-base, a community-curated resource describing the role of genes in pathogenic infection. PhytoPath provides access to genomic and phentoypic data from fungal and oomycete plant pathogens, and has enabled a considerable increase in the coverage of phytopathogen genomes in Ensembl Fungi and Ensembl Protists. PhytoPath also provides enhanced searching of the PHI-base resource as well as the fungi and protists in Ensembl Genomes.
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.
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GnpIS is a multispecies integrative information system dedicated to plant and fungi pests. It bridges genetic and genomic data, allowing researchers access to both genetic information (e.g. genetic maps, quantitative trait loci, association genetics, markers, polymorphisms, germplasms, phenotypes and genotypes) and genomic data (e.g. genomic sequences, physical maps, genome annotation and expression data) for species of agronomical interest. GnpIS is used by both large international projects and plant science departments at the French National Research Institute for Agriculture, Food and Environment. It is regularly improved and released several times per year. GnpIS is accessible through a web portal and allows to browse different types of data either independently through dedicated interfaces or simultaneously using a quick search ('google like search') or advanced search (Biomart, Galaxy, Intermine) tools.
The CPTAC Data Portal is the centralized repository for the dissemination of proteomic data collected by the Proteome Characterization Centers (PCCs) for the CPTAC program. The portal also hosts analyses of the mass spectrometry data (mapping of spectra to peptide sequences and protein identification) from the PCCs and from a CPTAC-sponsored common data analysis pipeline (CDAP).
EuPathDB (formerly ApiDB) is an integrated database covering the eukaryotic pathogens in the genera Acanthamoeba, Annacaliia, Babesia, Crithidia, Cryptosporidium, Edhazardia, Eimeria, Encephalitozoon, Endotrypanum, Entamoeba, Enterocytozoon, Giardia, Gregarina, Hamiltosporidium, Leishmania, Nematocida, Neospora, Nosema, Plasmodium, Theileria, Toxoplasma, Trichomonas, Trypanosoma and Vavraia, Vittaforma). While each of these groups is supported by a taxon-specific database built upon the same infrastructure, the EuPathDB portal offers an entry point to all of these resources, and the opportunity to leverage orthology for searches across genera.
The Barcode of Life Data Systems (BOLD) provides DNA barcode data. BOLD's online workbench supports data validation, annotation, and publication for specimen, distributional, and molecular data. The platform consists of four main modules: a data portal, a database of barcode clusters, an educational portal, and a data collection workbench. BOLD is the go-to site for DNA-based identification. As the central informatics platform for DNA barcoding, BOLD plays a crucial role in assimilating and organizing data gathered by the international barcode research community. Two iBOL (International Barcode of Life) Working Groups are supporting the ongoing development of BOLD.
With the creation of the Metabolomics Data Repository managed by Data Repository and Coordination Center (DRCC), the NIH acknowledges the importance of data sharing for metabolomics. Metabolomics represents the systematic study of low molecular weight molecules found in a biological sample, providing a "snapshot" of the current and actual state of the cell or organism at a specific point in time. Thus, the metabolome represents the functional activity of biological systems. As with other ‘omics’, metabolites are conserved across animals, plants and microbial species, facilitating the extrapolation of research findings in laboratory animals to humans. Common technologies for measuring the metabolome include mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), which can measure hundreds to thousands of unique chemical entities. Data sharing in metabolomics will include primary raw data and the biological and analytical meta-data necessary to interpret these data. Through cooperation between investigators, metabolomics laboratories and data coordinating centers, these data sets should provide a rich resource for the research community to enhance preclinical, clinical and translational research.
The BioImage Archive stores and distributes life sciences imaging datasets. It supports deposition of biological imaging data associated with publications for the whole research community, as well as reference imaging datasets. All data deposited to the BioImage Archive is made openly accessible to the scientific community.
Synapse is an open source software platform that clinical and biological data scientists can use to carry out, track, and communicate their research in real time. Synapse enables co-location of scientific content (data, code, results) and narrative descriptions of that work.
The 1000 Genomes Project is an international collaboration to produce an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts. This resource will support genome-wide association studies and other medical research studies. The genomes of about 2500 unidentified people from about 25 populations around the world will be sequenced using next-generation sequencing technologies. The results of the study will be freely and publicly accessible to researchers worldwide. The International Genome Sample Resource (IGSR) has been established at EMBL-EBI to continue supporting data generated by the 1000 Genomes Project, supplemented with new data and new analysis.
The UniProt Reference Clusters (UniRef) provide clustered sets of sequences from the UniProt Knowledgebase (including isoforms) and selected UniParc records in order to obtain complete coverage of the sequence space at several resolutions while hiding redundant sequences (but not their descriptions) from view.
The Database explores the interactions of chemicals and proteins. It integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins.
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Stemformatics is a collaboration between the stem cell and bioinformatics community. We were motivated by the plethora of exciting cell models in the public and private domains, and the realisation that for many biologists these were mostly inaccessible. We wanted a fast way to find and visualise interesting genes in these exemplar stem cell datasets. We'd like you to explore. You'll find data from leading stem cell laboratories in a format that is easy to search, easy to visualise and easy to export.