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Found 11 result(s)

Expressed Sequence Tags database

dbEST

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dbEST is a division of GenBank that contains sequence data and other information on "single-pass" cDNA sequences, or "Expressed Sequence Tags", from a number of organisms. Expressed Sequence Tags (ESTs) are short (usually about 300-500 bp), single-pass sequence reads from mRNA (cDNA). Typically they are produced in large batches. They represent a snapshot of genes expressed in a given tissue and/or at a given developmental stage. They are tags (some coding, others not) of expression for a given cDNA library. Most EST projects develop large numbers of sequences. These are commonly submitted to GenBank and dbEST as batches of dozens to thousands of entries, with a great deal of redundancy in the citation, submitter and library information. To improve the efficiency of the submission process for this type of data, we have designed a special streamlined submission process and data format. dbEST also includes sequences that are longer than the traditional ESTs, or are produced as single sequences or in small batches. Among these sequences are products of differential display experiments and RACE experiments. The thing that these sequences have in common with traditional ESTs, regardless of length, quality, or quantity, is that there is little information that can be annotated in the record. If a sequence is later characterized and annotated with biological features such as a coding region, 5'UTR, or 3'UTR, it should be submitted through the regular GenBank submissions procedure (via BankIt or Sequin), even if part of the sequence is already in dbEST. dbEST is reserved for single-pass reads. Assembled sequences should not be submitted to dbEST. GenBank will accept assembled EST submissions for the forthcoming TSA (Transcriptome Shotgun Assembly) division. The individual reads which make up the assembly should be submitted to dbEST, the Trace archive or the Short Read Archive (SRA) prior to the submission of the assemblies.

NCBI Structure

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The Structure database provides three-dimensional structures of macromolecules for a variety of research purposes and allows the user to retrieve structures for specific molecule types as well as structures for genes and proteins of interest. Three main databases comprise Structure-The Molecular Modeling Database; Conserved Domains and Protein Classification; and the BioSystems Database. Structure also links to the PubChem databases to connect biological activity data to the macromolecular structures. Users can locate structural templates for proteins and interactively view structures and sequence data to closely examine sequence-structure relationships.

OrtholugeDB

The Ortholog Database

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OrtholugeDB contains Ortholuge-based orthology predictions for completely sequenced bacterial and archaeal genomes. It is also a resource for reciprocal best BLAST-based ortholog predictions, in-paralog predictions (recently duplicated genes) and ortholog groups in Bacteria and Archaea. The Ortholuge method improves the specificity of high-throughput orthology prediction.

AlphaFold

AlphaFold Protein Structure Database

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AlphaFold DB provides open access to protein structure predictions for the human proteome and 20 other key organisms to accelerate scientific research.

iRefWeb

Interaction Reference Index Web Interface

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iRefWeb is an interface to a relational database containing the latest build of the interaction Reference Index (iRefIndex) which integrates protein interaction data from ten different interaction databases: BioGRID, BIND, CORUM, DIP, HPRD, INTACT, MINT, MPPI, MPACT and OPHID.

PhenoM

Phenomics of yeast Mutants

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<<<!!!<<< This repository is no longer available. >>>!!!>>>

NASC

The European Arabidopsis Stock Centre

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The Nottingham Arabidopsis Stock Centre (NASC) provides seed and information resources to Europe researchers.

UCSD Metabolomics Workbench

Metabolomics Workbench

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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.

NCBI PopSet

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NCBI PopSet collects DNA sequences to analyze the ways that populations are related by evolution. Such sequences indicate if populations originate from different members of the same species or from organisms of different species entirely.

Carbohydrate Structure Database

CSDB

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This is CSDB version 1 merged from Bacterial (BCSDB) and Plant&Fungal (PFCSDB) databases. This database aims at provision of structural, bibliographic, taxonomic, NMR spectroscopic and other information on glycan and glycoconjugate structures of prokaryotic, plant and fungal origin. It has been merged from the Bacterial and Plant&Fungal Carbohydrate Structure Databases (BCSDB+PFCSDB). The key points of this service are: High coverage. The coverage for bacteria (up to 2016) and archaea (up to 2016) is above 80%. Similar coverage for plants and fungi is expected in the future. The database is close to complete up to 1998 for plants, and up to 2006 for fungi. Data quality. High data quality is achieved by manual curation using original publications which is assisted by multiple automatic procedures for error control. Errors present in publications are reported and corrected, when possible. Data from other databases are verified on import. Detailed annotations. Structural data are supplied with extended bibliography, assigned NMR spectra, taxon identification including strains and serogroups, and other information if available in the original publication. Services. CSDB serves as a platform for a number of computational services tuned for glycobiology, such as NMR simulation, automated structure elucidation, taxon clustering, 3D molecular modeling, statistical processing of data etc. Integration. CSDB is cross-linked to other glycoinformatics projects and NCBI databases. The data are exportable in various formats, including most widespread encoding schemes and records using GlycoRDF ontology. Free web access. Users can access the database for free via its web interface (see Help). The main source of data is retrospective literature analysis. About 20% of data were imported from CCSD (Carbbank, University of Georgia, Athens; structures published before 1996) with subsequent manual curation and approval. The current coverage is displayed in red on the top of the left menu. The time lag between the publication of new data and their deposition into CSDB is ca. 1 year. In the scope of bacterial carbohydrates, CSDB covers nearly all structures of this origin published up to 2016. Prokaryotic, plant and fungal means that a glycan was found in the organism(s) belonging to these taxonomic domains or was obtained by modification of those found in them. Carbohydrate means a structure composed of any residues linked by glycosidic, ester, amidic, ketal, phospho- or sulpho-diester bonds in which at least one residue is a sugar or its derivative.

NCBI Nucleotide

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The NCBI Nucleotide database collects sequences from such sources as GenBank, RefSeq, TPA, and PDB. Sequences collected relate to genome, gene, and transcript sequence data, and provide a foundation for research related to the biomedical field.