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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://integromedb.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016. Search engine that integrates over 100 curated and publicly contributed data sources and provides integrated views on the genomic, proteomic, transcriptomic, genetic and functional information currently available. Information featured in the database includes gene function, orthologies, gene expression, pathways and protein-protein interactions, mutations and SNPs, disease relationships, related drugs and compounds.

Proper citation: IntegromeDB (RRID:SCR_004620) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/sites/entrez?db=geo

The GEO Profiles database stores gene expression profiles derived from curated GEO DataSets. Each Profile is presented as a chart that displays the expression level of one gene across all Samples within a DataSet. Experimental context is provided in the bars along the bottom of the charts making it possible to see at a glance whether a gene is differentially expressed across different experimental conditions. Profiles have various types of links including internal links that connect genes that exhibit similar behaviour, and external links to relevant records in other NCBI databases. GEO Profiles can be searched using many different attributes including keywords, gene symbols, gene names, GenBank accession numbers, or Profiles flagged as being differentially expressed.

Proper citation: Entrez GEO Profiles (RRID:SCR_004584) Copy   

•   Source: SciCrunch Registry

http://data.linkedct.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023.The Linked Clinical Trials (LinkedCT) project aims at publishing the first open Semantic Web data source for clinical trials data. The data exposed by LinkedCT is generated by (1) transforming existing data sources of clinical trials into RDF, and (2) discovering links between the records in the trials data and several other data sources. You may download static data dumps. The LinkedCT data space is published according to the principles of publishing Linked Data. These principles greatly enhance adaptability and usability of data on the web. Each entity in LinkedCT is identified by a unique HTTP dereferenceable Uniform Resource Identifier (URI). When the URI is looked up, related RDF statements about the entity is returned in HTML or RDF/XML based on the user''s agent. Moreover, a SPARQL endpoint is provided as the standard access method for RDF data.

Proper citation: LinkedCT (RRID:SCR_004585) Copy   

•   Source: SciCrunch Registry

http://www.yeastgenome.org/

A curated database that provides comprehensive integrated biological information for Saccharomyces cerevisiae along with search and analysis tools to explore these data. SGD allows researchers to discover functional relationships between sequence and gene products in fungi and higher organisms. The SGD also maintains the S. cerevisiae Gene Name Registry, a complete list of all gene names used in S. cerevisiae which includes a set of general guidelines to gene naming. Protein Page provides basic protein information calculated from the predicted sequence and contains links to a variety of secondary structure and tertiary structure resources. Yeast Biochemical Pathways allows users to view and search for biochemical reactions and pathways that occur in S. cerevisiae as well as map expression data onto the biochemical pathways. Literature citations are provided where available.

Proper citation: SGD (RRID:SCR_004694) Copy   

•   Source: SciCrunch Registry

http://zfin.org/action/antibody/search

The ZFIN Antibody Database is a database of zebrafish gene expression antibodies.

Proper citation: ZFIN Antibody Database (RRID:SCR_004729) Copy   

•   Source: SciCrunch Registry

http://pfam.xfam.org/

A database of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Users can analyze protein sequences for Pfam matches, view Pfam family annotation and alignments, see groups of related families, look at the domain organization of a protein sequence, find the domains on a PDB structure, and query Pfam by keywords. There are two components to Pfam: Pfam-A and Pfam-B. Pfam-A entries are high quality, manually curated families that may automatically generate a supplement using the ADDA database. These automatically generated entries are called Pfam-B. Although of lower quality, Pfam-B families can be useful for identifying functionally conserved regions when no Pfam-A entries are found. Pfam also generates higher-level groupings of related families, known as clans (collections of Pfam-A entries which are related by similarity of sequence, structure or profile-HMM).

Proper citation: Pfam (RRID:SCR_004726) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/mapview/map_search.cgi?taxid=7165

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. A database for the Anopheles gambiae str. PEST genome that was sequenced using a whole genome shotgun approach. The database aims to contribute to the understanding of mosquito genome structure and organization and will assist the development of malaria control strategies and improved anti-malarial drugs and vaccines. Sequences were generated and assembled into contigs for submission to GenBank.

Proper citation: Anopheles gambiae (African malaria mosquito) genome view (RRID:SCR_004402) Copy   

•   Source: SciCrunch Registry

http://www.uniprot.org/taxonomy/

NEWT is the taxonomy database maintained by the UniProt group. It integrates taxonomy data compiled in the NCBI database and data specific to the UniProt Knowledgebase. Browse by hierarchy, List all, or Complete proteomes. Organisms are classified in a hierarchical tree structure. Our taxonomy database contains every node (taxon) of the tree. UniProtKB taxonomy data is manually curated: next to manually verified organism names, we provide a selection of external links, organism strains and viral host information. Species with protein sequences stored in the UniProt Knowledgebase are named according to UniProt nomenclature. We endeavour to maintain a list of manually curated species names for which protein sequence data is available. In particular, we have adopted a systematic convention for naming viral and bacterial strains and isolates. Links to external sites are chosen by the UniProt taxonomy team and show pictures and various scientific data of interest (taxonomy, biology, physiology,...).

Proper citation: NEWT (RRID:SCR_004477) Copy   

•   Source: SciCrunch Registry

http://pluto3.nci.nih.gov/tissue/default.cfm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. The Specimen Resource Locator is a database to help researchers locate human specimens (tissue, serum, DNA/RNA, other specimens) for cancer research. It includes tissue banks and tissue procurement systems with access to normal, benign, precancerous and cancerous human tissue from a variety of organs. Researchers specify the types of specimens, number of cases, preservation methods and associated data they require. The Locator will then search the database and return a list of tissue resources most likely to meet their requirements. When no match is obtained, the researcher is referred to the NCI Tissue Expediter ([email protected]). The Tissue expediter is a scientist who can help researchers identify appropriate resources and/or appropriate collaborators.

Proper citation: NCI Specimen Resource Locator (RRID:SCR_004754) Copy   

•   Source: SciCrunch Registry

http://selectome.unil.ch/

Database of positive selection based on a rigorous branch-site specific likelihood test. Positive selection is detected using CODEML on all branches of animal gene trees.

Proper citation: Selectome: a Database of Positive Selection (RRID:SCR_004542) Copy   

•   Source: SciCrunch Registry

http://www.youtube.com/user/SacklerColloquia#g/u

This is the Sackler Colloquia YouTube channel. The Arthur M. Sackler Colloquia of the National Academy of Sciences address scientific topics of broad and current interest, cutting across the boundaries of traditional disciplines. Each year, several colloquia are scheduled, typically two days in length and international in scope. Each colloquium is organized by a member of the Academy, often with the assistance of an organizing committee, and feature presentations by leading scientists in the field and discussions with a hundred or more researchers with an interest in the topic. These colloquia are made possible by a generous gift from Jill Sackler, in memory of her husband, Arthur M. Sackler.

Proper citation: Sackler Colloquia's YouTube Channel (RRID:SCR_005126) Copy   

•   Source: SciCrunch Registry

http://stellabase.org

StellaBase is a genomics database of Nematostella vectensis. It allows users to query the assembled Nematostella genome, a confirmed gene library, and a predicted genome using both keyword and homology based search functions. Data provided by these searches will elucidate gene family evolution in early animals. Unique research tools, including a Nematostella genetic stock library, a primer library, a literature repository and a gene expression library will provide support to the burgeoning Nematostella research community. Supported by: National Science Foundation (Grant No. 0212773 to JRF)

Proper citation: StellaBase: Nematostella vactensis genomics database (RRID:SCR_005153) 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.ncbi.nlm.nih.gov/biosample

Database containing descriptions of biological source materials used in experimental assays. Sources include: GenBank, Sequence Read Archive (SRA), Coriell, ATCC. Submissions are supported by a web-based Submission Portal that guides users through a series of forms for input of rich metadata describing their samples. As the capacity and complexity of biological data sets expands, databases face new challenges in ensuring that the information is adequately organized and described. The NCBI BioSample database is being developed to help address the challenges by providing the means by which data generators can organize and describe a broad range of sample types, and link to corresponding sets of experimental data in archival databases.

Proper citation: NCBI BioSample (RRID:SCR_004854) Copy   

•   Source: SciCrunch Registry

http://rnp.uthscsa.edu/rnp/SRPDB/SRPDB.html

It provides aligned, annotated and phylogenetically ordered sequences related to structure and function of SRP. SRPDB assists the study of structure and function of signal recognition particles (SRP), and provides annotated SRP, RNA, and SRP protein sequences phylogenetically ordered and aligned. Included are representative RNA secondary structure diagrams where each base pair is proven by comparative sequence analysis, information about other proteins that play a role in SRP-mediated protein translocation, as well as structural information about components of SRP. Where possible, links to primary sources were established.

Proper citation: SRPDB (RRID:SCR_005142) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/Structure/ibis/ibis.cgi

A web server and database that organizes, analyzes and predicts interactions between proteins and other biomolecules. For a given protein sequence or structure query, it reports protein-protein, protein-small molecule, protein nucleic acids and protein-ion interactions observed in experimentally-determined structural biological assemblies. It also infers/predicts interacting partners and binding sites by homology, by inspecting the protein complexes formed by close homologs of a given query. To ensure biological relevance of inferred binding sites, the IBIS algorithm clusters binding sites formed by homologs based on binding site sequence and structure conservation.

Proper citation: IBIS: Inferred Biomolecular Interactions Server (RRID:SCR_004886) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/jpopgen/dbNSFP

A database for functional prediction and annotation of all potential non-synonymous single-nucleotide variants (nsSNVs) in the human genome. Version 2.0 is based on the Gencode release 9 / Ensembl version 64 and includes a total of 87,347,043 nsSNVs and 2,270,742 essential splice site SNVs. It compiles prediction scores from six prediction algorithms (SIFT, Polyphen2, LRT, MutationTaster, MutationAssessor and FATHMM), three conservation scores (PhyloP, GERP++ and SiPhy) and other related information including allele frequencies observed in the 1000 Genomes Project phase 1 data and the NHLBI Exome Sequencing Project, various gene IDs from different databases, functional descriptions of genes, gene expression and gene interaction information, etc. Some dbNSFP contents (may not be up-to-date though) can also be accessed through variant tools, ANNOVAR, KGGSeq, UCSC Genome Browser''s Variant Annotation Integrator, Ensembl Variant Effect Predictor and HGMD.

Proper citation: dbNSFP (RRID:SCR_005178) Copy   

•   Source: SciCrunch Registry

http://mlstoslo.uio.no/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11,2023. SuperCAT hosts typing databases for the Bacillus cereus group of bacteria. The databases contain MultiLocus Sequence Typing (MLST), MultiLocus Enzyme Electrophoresis (MLEE), and Amplified Fragment Length Polymorphism (AFLP) phylogenetic data. multilocus, sequence, Bacillus cereus, bacteria, Genomics, non-vertebrate, taxonomy, identification

Proper citation: SuperCAT (RRID:SCR_004882) Copy   

•   Source: SciCrunch Registry

http://oger.tu-bs.de/strepto_db

A database for comparative genomics of group A and group B streptococci. It is based on OGeR (Open Genome Resource for comparative analysis of prokaryotic genomes) and includes all sequenced GAS and GBS strains and serovars available as EMBL genome review or NCBI GenBank files. Strepto-DB identifies the homologous proteins deduced from the genomes of interest. It allows for the elucidation of the GAS and GBS core- and pan-genomes via genome-wide comparisons. Moreover, an intergenic region analysis tool provides alignments and predictions for transcription factor binding sites in the non-coding sequences. An interactive genome browser visualizes functional annotations. Strepto-DB (http://oger.tu-bs.de/strepto_db) was created by the use of OGeR, the Open Genome Resource for comparative analysis of prokaryotic genomes. OGeR is a newly developed open source database and tool platform for the web-based storage, distribution, visualization and comparison of prokaryotic genome data. The system automatically creates the dedicated relational database and web interface and imports an arbitrary number of genomes derived from standardized genome files.

Proper citation: Strepto-DB (RRID:SCR_005196) Copy   

•   Source: SciCrunch Registry