PROSITE is a database of protein families and domains. It consists of biologically significant sites, patterns and profiles that help to reliably identify to which known protein family a new sequence belongs. PROSITE is based at the Swiss Institute of Bioinformatics (SIB), Geneva, Switzerland.

SFLD (Structure-Function Linkage Database) is a hierarchical classification of enzymes that relates specific sequence-structure features to specific chemical capabilities.

Database that aggregates sample information for reference samples (e.g. Coriell Cell lines) and samples for which data exist in one of the EBI''''s assay databases such as ArrayExpress, the European Nucleotide Archive or PRoteomics Identificates DatabasE. It provides links to assays for specific samples, and accepts direct submissions of sample information. The goals of the BioSample Database include: # recording and linking of sample information consistently within EBI databases such as ENA, ArrayExpress and PRIDE; # minimizing data entry efforts for EBI database submitters by enabling submitting sample descriptions once and referencing them later in data submissions to assay databases and # supporting cross database queries by sample characteristics. The database includes a growing set of reference samples, such as cell lines, which are repeatedly used in experiments and can be easily referenced from any database by their accession numbers. Accession numbers for the reference samples will be exchanged with a similar database at NCBI. The samples in the database can be queried by their attributes, such as sample types, disease names or sample providers. A simple tab-delimited format facilitates submissions of sample information to the database, initially via email to biosamples (at) ebi.ac.uk. Current data sources: * European Nucleotide Archive (424,811 samples) * PRIDE (17,001 samples) * ArrayExpress (1,187,884 samples) * ENCODE cell lines (119 samples) * CORIELL cell lines (27,002 samples) * Thousand Genome (2,628 samples) * HapMap (1,417 samples) * IMSR (248,660 samples)

Various non-redundant databases with different sequence identity cut-offs created by clustering closely similar sequences to yield a representative subset of sequences. In the UniRef90 and UniRef50 databases no pair of sequences in the representative set has >90% or >50% mutual sequence identity. The UniRef100 database presents identical sequences and sub-fragments as a single entry with protein IDs, sequences, bibliography, and links to protein databases. The two major objectives of UniRef are: (i) to facilitate sequence merging in UniProt, and (ii) to allow faster and more informative sequence similarity searches. Although the UniProt Knowledgebase is much less redundant than UniParc, it still contains a certain level of redundancy because it is not possible to use fully automatic merging without risking merging of similar sequences from different proteins. However, such automatic procedures are extremely useful in compiling the UniRef databases to obtain complete coverage of sequence space while hiding redundant sequences (but not their descriptions) from view. A high level of redundancy results in several problems, including slow database searches and long lists of similar or identical alignments that can obscure novel matches in the output. Thus, a more even sampling of sequence space is advantageous. You may access NREF via the FTP server.

HAMAP stands for High-quality Automated and Manual Annotation of Proteins. HAMAP profiles are manually created by expert curators. They identify proteins that are part of well-conserved protein families or subfamilies. HAMAP is based at the SIB Swiss Institute of Bioinformatics, Geneva, Switzerland.

This dataset contains INSDC sequence records not associated with environmental sample identifiers or host organisms. The dataset is prepared periodically using the public ENA API (https://www.ebi.ac.uk/ena/portal/api/) by querying data with search parameters: `environmental_sample=False & host=""`

EMBL-EBI also publishes other records in separate datasets (https://www.gbif.org/publisher/ada9d123-ddb4-467d-8891-806ea8d94230).

The data was then processed as follows:

1. Human sequences were excluded.

2. For non-CONTIG records, the sample accession number (when available) along with the scientific name were used to identify sequence records corresponding to the same individuals (or group of organism of the same species in the same sample). Only one record was kept for each scientific name/sample accession number.

3. Contigs and whole genome shotgun (WGS) records were added individually.

4. The records that were missing some information were excluded. Only records associated with a specimen voucher or records containing both a location AND a date were kept.

5. The records associated with the same vouchers are aggregated together.

6. A lot of records left corresponded to individual sequences or reads corresponding to the same organisms. In practise, these were "duplicate" occurrence records that weren't filtered out in STEP 2 because the sample accession sample was missing. To identify those potential duplicates, we grouped all the remaining records by `scientific_name`, `collection_date`, `location`, `country`, `identified_by`, `collected_by` and `sample_accession` (when available). Then we excluded the groups that contained more than 50 records. The rationale behind the choice of threshold is explained here: https://github.com/gbif/embl-adapter/issues/10#issuecomment-855757978

7. To improve the matching of the EBI scientific name to the GBIF backbone taxonomy, we incorporated the ENA taxonomic information. The kingdom, Phylum, Class, Order, Family, and genus were obtained from the ENA taxonomy checklist available here: http://ftp.ebi.ac.uk/pub/databases/ena/taxonomy/sdwca.zip

More information available here: https://github.com/gbif/embl-adapter#readme

You can find the mapping used to format the EMBL data to Darwin Core Archive here: https://github.com/gbif/embl-adapter/blob/master/DATAMAPPING.md

Repository for electron microscopy density maps of macromolecular complexes and subcellular structures at Protein Data Bank in Europe. Covers techniques, including single-particle analysis, electron tomography, and electron (2D) crystallography.

Context

ChEMBL is maintained by the European Bioinformatics Institute (EBI), of the European Molecular Biology Laboratory (EMBL), based at the Wellcome Trust Genome Campus, Hinxton, UK.

Content

ChEMBL is a manually curated database of bioactive molecules with drug-like properties used in drug discovery, including information about existing patented drugs.

Schema: http://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_23/chembl_23_schema.png

Documentation: http://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_23/schema_documentation.html

Fork this notebook to get started on accessing data in the BigQuery dataset using the BQhelper package to write SQL queries.

Acknowledgements

“ChEMBL” by the European Bioinformatics Institute (EMBL-EBI), used under CC BY-SA 3.0. Modifications have been made to add normalized publication numbers.

Data Origin: https://bigquery.cloud.google.com/dataset/patents-public-data:ebi_chembl

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Dbfetch is an acronym for database fetch. Dbfetch provides an easy way to retrieve entries from various databases at the EBI in a consistent manner and allows you to retrieve up to 50 entries at a time from various up-to-date biological databases. It can be used from any browser as well as well as within a web-aware scripting tool that uses wget, lynx or similar. From the browser, follow these instructions... * Select a database: If you are using the first form to paste your search items: choose a database name from this form. If you are using the second form to upload your search items: the database name is included at the beginning of each line line of the upload file followed by a colon. * Enter search terms: These MUST BE in the appropriate database format, up to 200 search items can be queried in one run. If you are using the first form: separate search items with a comma or space. If you are using the second form: separate search items with a new line. * Choose an output format: Here you can choose the simpler fasta format, or the databases'''' default format for the chosen database. * Style: You can get your results as text or html. * Retrieve! - You are now ready to fetch your results, by pressing the Retrieve button.

Get the latest USA Sushi Ebi import data with importer names, shipment details, buyers list, product description, price, quantity, and major US ports.

SMART (a Simple Modular Architecture Research Tool) allows the identification and annotation of genetically mobile domains and the analysis of domain architectures. SMART is based at EMBL, Heidelberg, Germany.

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The EBI SRS server is a primary gateway to major databases in the field of molecular biology produced and supported at EBI as well as European public access point to the MEDLINE database provided by US National Library of Medicine (NLM). It is a reference server for latest developments in data and application integration. Features include: concept of virtual databases, integration of XML databases like the Integrated Resource of Protein Domains and Functional Sites (InterPro), Gene Ontology (GO), MEDLINE, Metabolic pathways, etc., user friendly data representation in ''Nice views'', SRSQuickSearch bookmarklets. Quick Searches allow users to make a number of searches without needing to learn how to use SRS in depth. The searches query some of the common databanks without having to go and select them explicitly and without the need to understand the SRS Query Forms. Quick Searches can be performed from either the Start page (when you first open SRS) or the SRS Quick Search page (when you are already in a project). SRS also has the ability to search for links between your current results and related information in other databanks. Additionally, it is able to analyze the results of your search using many bioinformatics analysis tools or applications. This enables you to seek out further information that may be relevant to your initial search.

The EBI genomes pages give access to a large number of complete genomes including bacteria, archaea, viruses, phages, plasmids, viroids and eukaryotes. Methods using whole genome shotgun data are used to gain a large amount of genome coverage for an organism. WGS data for a growing number of organisms are being submitted to DDBJ/EMBL/GenBank. Genome entries have been listed in their appropriate category which may be browsed using the website navigation tool bar on the left. While organelles are all listed in a separate category, any from Eukaryota with chromosome entries are also listed in the Eukaryota page. Within each page, entries are grouped and sorted at the species level with links to the taxonomy page for that species separating each group. Within each species, entries whose source organism has been categorized further are grouped and numbered accordingly. Links are made to: * taxonomy * complete EMBL flatfile * CON files * lists of CON segments * Project * Proteomes pages * FASTA file of Proteins * list of Proteins

PRINTS is a compendium of protein fingerprints. A fingerprint is a group of conserved motifs used to characterise a protein family or domain. PRINTS is based at the University of Manchester, UK.

Get the latest USA Ebi import data with importer names, shipment details, buyers list, product description, price, quantity, and major US ports.

Rfam is a database of RNA sequence and structure families. The database contains information on families and sequences of constituent members which can be searched by keyword or taxonomy. Data can also be downloaded via FTP.

Data deposited on the European Bioinformatics Insititute (EBI) database under accession number E-MTAB- 11727 (https://www.ebi.ac.uk/arrayexpress/experiments/ E-MTAB-11727)

Hepatocyte-controlled availability of activated TGFb reprograms macrophage polarization affecting liver injury and regeneration.

Samples in SEEK (ArrayExpress-compliant sample type https://seek.lisym.org/sample_types/21)

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This fileset provides supporting data and corpora for the empirical study described in:Rafael S. Gonçalves and Mark A. Musen. The variable quality of metadata about biological samples used in biomedical experiments. Scientific Data, in press (2019).Description of filesAnalysis spreadsheet files:- ncbi-biosample-metadata-study.xlsx contains data to support the analysis of the quality of metadata in the NCBI BioSample.- ebi-biosamples-metadata-study.xlsx contains data to support the analysis of the quality of metadata in the EBI BioSamples.Validation data files:- ncbi-biosample-validation-data.tar.gz is an archive containing the validation data for the analysis of the entire NCBI BioSample dataset.- ncbi-biosample-packaged-validation-data.tar.gz is an archive containing the validation data for the analysis of the subset of metadata records in the NCBI BioSample that use a BioSample package definition.- ebi-ncbi-shared-records-validation-data.tar.gz is an archive containing the validation data for the analysis of the set of metadata records that exist both in EBI BioSamples and NCBI BioSample.Corpus files:- ebi-biosamples-corpus.xml.gz corresponds to the EBI BioSamples corpus.- ncbi-biosample-corpus.xml.gz corresponds to the NCBI BioSample corpus.- ncbi-biosample-packaged-records-corpus.tar.gz corresponds to the NCBI BioSample metadata records that declare a package definition.- ebi-ncbi-shared-records-corpus.tar.gz corresponds to the corpus of metadata records that exist both in NCBI BioSample and EBI BioSamples.

Protein-Protein, Genetic, and Chemical Interactions for Lim YM (2012):Ebi/AP-1 suppresses pro-apoptotic genes expression and permits long-term survival of Drosophila sensory neurons. curated by BioGRID (https://thebiogrid.org); ABSTRACT: Sensory organs are constantly exposed to physical and chemical stresses that collectively threaten the survival of sensory neurons. Failure to protect stressed neurons leads to age-related loss of neurons and sensory dysfunction in organs in which the supply of new sensory neurons is limited, such as the human auditory system. Transducin β-like protein 1 (TBL1) is a candidate gene for ocular albinism with late-onset sensorineural deafness, a form of X-linked age-related hearing loss. TBL1 encodes an evolutionarily conserved F-box-like and WD40 repeats-containing subunit of the nuclear receptor co-repressor/silencing mediator for retinoid and thyroid hormone receptor and other transcriptional co-repressor complexes. Here we report that a Drosophila homologue of TBL1, Ebi, is required for maintenance of photoreceptor neurons. Loss of ebi function caused late-onset neuronal apoptosis in the retina and increased sensitivity to oxidative stress. Ebi formed a complex with activator protein 1 (AP-1) and was required for repression of Drosophila pro-apoptotic and anti-apoptotic genes expression. These results suggest that Ebi/AP-1 suppresses basal transcription levels of apoptotic genes and thereby protects sensory neurons from degeneration.