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http://www.ebi.ac.uk/asd/altextron/indexhtml

THIS RESOURCE IS NO LONGER IN SERVICE. A computer generated high quality dataset of human transcript-confirmed constitutive and alternative exons and introns. The alternative events have been delineated and annotated with various characterizations. AltExtron is the prototype database for the production version AltSplice. AltExtron is more geared towards investigating various aspects of the methodologies used, and focuses in general on the biology behind alternative splicing. The complete data used in this work is available for downloading in several flat files, containing human genes, introns, exons, isoform events, human-mouse comparisons, and additional information on GC-AG introns. Two versions of AltExtron data are available - one as prototype (for human) and another as latest build (for human, drosophila, mouse, and others) based on EMBL/GenBank (Feb 2003).

Proper citation: AltExtron Database (RRID:SCR_008404) Copy   

•   Source: SciCrunch Registry
  

http://identifiers.org/

A system providing resolvable persistent Uniform Resource Identifiers (URIs) used to identify data for the scientific community, with a current focus on the Life Sciences domain. The provision of resolvable identifiers (URLs) fits well with the Semantic Web vision, and the Linked Data initiative. It provides direct access to the identified data using one chosen physical location (or resource). If more than one physical locations providing the data are recorded in the Registry, then you can access them via the top banner or by using a profile.

Proper citation: Identifiers.org (RRID:SCR_003735) Copy   

•   Source: SciCrunch Registry
  

http://www.ebi.ac.uk/Tools/dbfetch/dbfetch

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.

Proper citation: EBI Dbfetch (RRID:SCR_004393) Copy   

•   Source: SciCrunch Registry
  

http://www.ebi.ac.uk/thornton-srv/databases/profunc/index.html

The ProFunc server had been developed to help identify the likely biochemical function of a protein from its three-dimensional structure. It uses both sequence- and structure-based methods including fold matching, residue conservation, surface cleft analysis, and functional 3D templates, to identify both the protein''''s likely active site and possible homologues in the PDB. Often, where one method fails to provide any functional insight another may be more helpful. You can submit your own structure, analyze an existing PDB entry, or retrieve the results of a previously submitted run. The files are usually stored for about 6 months before being deleted. However, they are stored on a partition that is not backed up; so, in principle, they could disappear at any time.

Proper citation: ProFunc (RRID:SCR_004450) Copy   

•   Source: SciCrunch Registry
  

http://www.ebi.ac.uk/biosamples/

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)

Proper citation: BioSample Database at EBI (RRID:SCR_004856) Copy   

•   Source: SciCrunch Registry
  

http://www.ebi.ac.uk/expressionprofiler/

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The EP:GO browser is built into EBI's Expression Profiler, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice.

Proper citation: Expression Profiler (RRID:SCR_005821) Copy   

•   Source: SciCrunch Registry
  

http://www.ebi.ac.uk/thornton-srv/databases/FunTree/

FunTree provides a range of data resources to detect the evolution of enzyme function within distant structurally related clusters within domain super families as determined by CATH. To access the resource enter a specific CATH superfamily code or search for a structure / sequence / function (either via a EC code or KEGG ligand / reaction ID, PDB ID or UniProtKB ID). Or browse the resource via superfamily / function / structure / metabolites & reactions via the menu on the left panel. FunTree is a new resource that brings together sequence, structure, phylogenetic, chemical and mechanistic information for structurally defined enzyme superfamilies. Gathering together this range of data into a single resource allows the investigation of how novel enzyme functions have evolved within a structurally defined superfamily as well as providing a means to analyse trends across many superfamilies. This is done not only within the context of an enzyme''''s sequence and structure but also the relationships of their reactions. Developed in tandem with the CATH database, it currently comprises 276 superfamilies covering 1800 (70%) of sequence assigned enzyme reactions. Central to the resource are phylogenetic trees generated from structurally informed multiple sequence alignments using both domain structural alignments supplemented with domain sequences and whole sequence alignments based on commonality of multi-domain architectures. These trees are decorated with functional annotations such as metabolite similarity as well as annotations from manually curated resources such the catalytic site atlas and MACiE for enzyme mechanisms.

Proper citation: FunTree (RRID:SCR_006014) Copy   

•   Source: SciCrunch Registry
  

http://www.ebi.ac.uk/thornton-srv/databases/drugport/

DrugPort provides an analysis of the structural information available in the Protein Data Bank (PDB) relating to drug molecules and their protein targets. The drug-target data comes from the DrugBank database. You can search the entries by identifier, test or by protein sequence, or you can use the browse options in the menu on the left.

Proper citation: DrugPort (RRID:SCR_006573) Copy   

•   Source: SciCrunch Registry
  

http://www.ebi.ac.uk/sbo/

A set of controlled, relational vocabularies of terms commonly used in Systems Biology, and in particular in computational modeling. The ontology consists of seven orthogonal vocabularies defining: the roles of reaction participants (eg. substrate), quantitative parameters (eg. Michaelis constant), a precise classification of mathematical expressions that describe the system (eg. mass action rate law), the modeling framework used (eg. logical framework), and a branch each to describe entity (eg. macromolecule) and interaction (eg. process) types, and a branch to define the different types of metadata that may be present within a model. SBO terms can be used to introduce a layer of semantic information into the standard description of a model, or to annotate the results of biochemical experiments in order to facilitate their efficient reuse. SBO is an Open Biomedical Ontologies (OBO) candidate ontology, and is free for use. A programmatic access to the content of the Systems Biology Ontology is provided by Web Services.

Proper citation: SBO (RRID:SCR_006753) Copy   

•   Source: SciCrunch Registry
  

http://www.ebi.ac.uk/Tools/msa/muscle/

Multiple sequence alignment method with reduced time and space complexity.Multiple sequence alignment with high accuracy and high throughput. Data analysis service for multiple sequence comparison by log- expectation.

Proper citation: MUSCLE (RRID:SCR_011812) Copy   

•   Source: SciCrunch Registry
  

http://www.biolayout.org

BioLayout Express3D is a powerful new tool for the visualization and analysis of networks derived from biological systems. Network-based approaches are becoming increasing popular for the analysis of ''omics and other high dimensional data. Networks can be produced from a wide variety of biological relationships, such as interactions between individuals, disease transmission, sequence similarity, metabolic pathways, protein interactions, pathways, regulatory cascades, gene expression, etc. BioLayout Express3D has been specifically designed for visualization, clustering and analysis of large network graphs in two- and three-dimensional space derived primarily, but not exclusively, from biological data. Sponsors: This resource is supported by BBSRC (BB / F003722 / 1) and the Wellcome Trust (GR077040RP). Keywords: Biology, Tool, Software, visualization, Analysis, Network, Biological, System, Dimentional, Data, Disease, Transmission, Sequence, Metabolic, Pathway, Protein, Interaction, Gene, Expression, Clustering, Analysis,

Proper citation: BioLayout Express 3D (RRID:SCR_007179) Copy   

•   Source: SciCrunch Registry
  

http://www.bioconductor.org/packages/release/bioc/html/HTqPCR.html

Software package for the analysis of Ct values from high throughput quantitative real-time PCR (qPCR) assays across multiple conditions or replicates. The input data can be from spatially-defined formats such ABI TaqMan Low Density Arrays or OpenArray; LightCycler from Roche Applied Science; the CFX plates from Bio-Rad Laboratories; conventional 96- or 384-well plates; or microfluidic devices such as the Dynamic Arrays from Fluidigm Corporation. HTqPCR handles data loading, quality assessment, normalization, visualization and parametric or non-parametric testing for statistical significance in Ct values between features (e.g. genes, microRNAs).

Proper citation: HTqPCR (RRID:SCR_003375) Copy   

•   Source: SciCrunch Registry
  

http://www.virtualflybrain.org

An interactive tool for neurobiologists to explore the detailed neuroanatomy, neuron connectivity and gene expression of the adult Drosophila melanogaster brain.

Proper citation: Virtual Fly Brain (RRID:SCR_004229) Copy   

•   Source: SciCrunch Registry
  

http://bioinformatics.oxfordjournals.org/content/21/19/3806.long

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 26, 2016. A data environment for computational research in comparative and functional genomics, designed to address issues of consistency, reproducibility, scalability and accessibility., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CoGenT++ (RRID:SCR_000249) Copy   

•   Source: SciCrunch Registry
  

http://www.uniprot.org/

Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.

Proper citation: UniProt (RRID:SCR_002380) Copy   

•   Source: SciCrunch Registry
  

http://purl.bioontology.org/ontology/ORDO

Ontology to provide a structured vocabulary for rare diseases capturing relationships between diseases, genes and other relevant features which will form a useful resource for the computational analysis of rare diseases. It derived from the Orphanet database (http://www.orpha.net) , a multilingual database dedicated to rare diseases populated from literature and validated by international experts. It integrates a nosology (classification of rare diseases), relationships (gene-disease relations, epiemological data) and connections with other terminologies (MeSH, SNOMED CT, UMLS, MedDRA), databases (OMIM, UniProtKB, HGNC, ensembl, Reactome, IUPHAR, Geantlas) or classifications (ICD10). The ontology will be maintained by Orphanet and further populated with new data. Orphanet classifications can be browsed in the OLS view. The Orphanet Rare Disease Ontology is updated monthly and follows the OBO guidelines on deprecation of terms. It constitutes the official ontology of rare diseases produced and maintained by Orphanet (INSERM, US14).

Proper citation: Orphanet Rare Disease Ontology (RRID:SCR_010402) Copy   

•   Source: SciCrunch Registry
  

http://www.ebi.ac.uk/Tools/sss/wublast/

Tool to find regions of sequence similarity within selected protein databases quickly, with minimum loss of sensitivity.

Proper citation: WU-BLAST (RRID:SCR_011824) Copy   

•   Source: SciCrunch Registry
  

http://orchem.sourceforge.net

OrChem is an extension for the Oracle 11G database that adds registration and indexing of chemical structures to support fast substructure and similarity searching. The cheminformatics functionality is provided by the Chemistry Development Kit. OrChem provides similarity searching with response times in the order of seconds for databases with millions of compounds, depending on a given similarity cut-off. For substructure searching, it can make use of multiple processor cores on today''s powerful database servers to provide fast response times in equally large data sets. OrChem is an Oracle chemistry plug-in using the Chemistry Development Kit (CDK). The CDK is an open source Java library for Chemoinformatics and Bioinformatics. OrChem is maintained by the chemoinformatics and metabolism team of the European Bioinformatics Institute. Oracle Data cartridges extend the capabilities of the Oracle server. For chemistry various commercial cartridges exist that facilitate searching and analyzing chemical data. OrChem also provides functionality like this, but is not a cartridge. It doesn''t need Oracle''s extensibility architecture because its Java components run as Java stored procedures inside the Oracle standard JVM (Aurora). OrChem is suitable for Oracle 11G and onwards. Starting with Oracle 11g release 1 (11.1) there is a just-in-time(JIT) compiler for Oracle JVM environment. A JIT compiler for Oracle JVM enables much faster execution because it manages the invalidation, recompilation, and storage of code without an external mechanism. This new Oracle feature makes Java classes perform better than before.

Proper citation: OrChem (RRID:SCR_008865) Copy   

•   Source: SciCrunch Registry
  

http://ftp://ftp.ebi.ac.uk/pub/databases/pombase/pombe/Protein_data/

FTP site to access Schizosaccharomyces pombe protein data.

Proper citation: Pompep (RRID:SCR_010536) Copy   

•   Source: SciCrunch Registry
  

http://www.ebi.ac.uk/genomes

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

Proper citation: EBI Genomes (RRID:SCR_002426) Copy   

•   Source: SciCrunch Registry