Searching the RRID Resource Information Network
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
HubMed provides an interface to PubMed. Quick access to searches with a Firefox search plugin or a HubMed bookmarklet (drag to your browser''s bookmarks toolbar). Export citations in RIS, BibTeX, RDF and MODS formats, or directly to RefWorks. Unzip HubMed''s import filter into Endnote''s Filters folder for direct import into Endnote, or install the RIS Export plugin for direct import into ProCite, RefMan and older versions of Endnote. Use the Citation Finder to convert reference lists from PDFs into search results. Create lists of closely related papers using Rank Relations, then visualise and browse clusters of related papers using TouchGraph (requires Java). Graph occurrences of keywords in published papers over time. Tag and store annotated metadata for articles of interest.
Proper citation: HubMed (RRID:SCR_007296) Copy
http://genome.mc.pref.osaka.jp/BGED/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 08, 2011. This database contains gene expression data for various physiological and pathological processes in mouse brain. All the data have been obtained by adaptor-tagged competitive PCR, an advanced version of quantitative PCR. Brain Gene Expression Database (BGED) contains gene expression data for various physiological and pathological processes in mouse brain. All the data have been obtained by adaptor-tagged competitive PCR, an advanced version of quantitative PCR. Manual Download 1. Data retrieval Gene expression data can be retrieved either by ID numbers or by keywords representing functional annotations from this page. The ID numbers include GenBank, RefSeq, SwissProt, Gene Ontology, and BED (our own ID). The keyword search is based either on definition in GenBank, SwissProt and RefSeq, functional annotation of SwissProt database, or Gene Ontology terms. 2. Gene expression pattern display * Display of multiple gene expression patterns. Expression patterns of multiple genes selected by the keyword search can be displayed from the result page of the keyword search. * Gene expression pattern similarity search This function is available on the information page of each gene accessed through BED ID (in-house ID).
Proper citation: Brain Gene Expression Database (RRID:SCR_007299) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 26, 2016. CoC Central is a searchable database of residue conservation data covering the universe of known protein structures. CoC is useful for identifying functionally, kinetically, and thermodynamically important residues. Knowledge of universally conserved positions in protein folds may aid in identifying positions of kinetic or thermodynamic importance in protein folding, as well as those with a functional role.
Proper citation: CoC Central (RRID:SCR_007602) Copy
https://bioinformatics.cs.vt.edu/cmgs/CMGSDB/
CMGSDB is a database whose objective is to investigate gene silencing from a computational perspective using tools of computational biology and bioinformatics. The database is C. elegans centric, although the schema is suitable for any organism and can be extended with minor changes to support multiple organisms. CMGSDB contains details of genome annotation data (chromosomes, genes, coding transcripts), protein structure data (secondary structure, physical properties), microarray expression data (genomewide gene expressions for over 500 microarray experiments), RNA interferance data (RNAi experiment details, phenotypes exhibited by genes in different experiments, phenotype hierarchy and associations between them), protein-protein interaction data, and gene-regulation data.
Proper citation: CMGSDB- Computational Models for Gene Silencing (RRID:SCR_007601) Copy
COGEME is an ongoing BBSRC-funded study to construct a relational database of genomic information from phytopathogenic fungi. This site also hosts microarray data for Blumeria graminis. Expressed sequence tags (ESTs) obtained from eighteen species of plant pathogenic fungi, two species of phytopathogenic oomycete and three species of saprophytic fungi are included here. Hierarchical clustering software was used to classify together ESTs representing the same gene and produce a single contig, or consensus sequence. The unisequence set for each pathogen therefore represents a set of unique gene sequences, each one consisting of either a single EST or a contig sequence made from a group of ESTs. Unisequences were annotated based on top hits against the NCBI non-redundant protein database using blastx.
Proper citation: COGEME Phytopathogenic Fungi and Oomycete EST Database (RRID:SCR_007604) Copy
http://ppa.bcf.ku.edu/DB_PABP/
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. DB-PABP is an attempt to document the publicly available experimentally determined polyanion binding proteins (PABPs). The purpose of the database is to provide life scientists who are interested in PA/PABP interactions with a comprehensive data repository, as well as computer scientists with a publicly available dataset to perform knowledge discovery and datamining studies. The database is manually curated. It uses protein annotations from NCBI protein database and literature information is retrieved from PubMed. Whenever applicable, links to NCBI protein database and PubMed are provided so users may access additional information available in these public databases.
Proper citation: DB-PABP: a database of polyanion binding proteins (RRID:SCR_007603) Copy
http://www.proteomicsresource.org/default.aspx
Biodefense Proteomics Resource Center presents information on Class A-C biodefense organisms. :This list includes Bacillus anthracis, Brucella abortus, Francisella tularensis, salmonella typhi, salmonella typhimurium, Virbio cholerae, Yersinia pestis, Cryptosporidium parvum, Toxoplasma gondii, Avian influenza, SARS, Monkeypox, Vaccinia, and Variola. For each organism, the page provides a general overview of the organism and the diseases it causes, protein (and protein interaction) data, reagents, and data from experiments performed with this organism. Users may also find links to the NCBI Taxonomy center.
Proper citation: Biodefense Proteomics Resource Center (RRID:SCR_007564) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented June 24, 2013 as per the Miriam database (http://www.ebi.ac.uk/miriam/main/collections/MIR:00000021). The CluSTr database offers an automatic classification of UniProt Knowledgebase and IPI proteins into groups of related proteins. The clustering is based on analysis of all pairwise comparisons between protein sequences. The database provides links to InterPro, which integrates information on protein families, domains and functional sites from PROSITE, PRINTS, Pfam, ProDom, SMART, TIGRFAMs, Gene3D, SUPERFAMILY, PIR Superfamily and PANTHER. To date (2011), CluSTr contains the following information: * 9,450,285 sequences from UniProt Knowledgebase release 15.6 * 308,281 sequences from IPI * 3,636,831,744 similarities, with pairwise alignments generated on-the-fly * 17,616,060 clusters * Clustering for 972 organisms with completely sequenced genomes. For the full list of the genomes see Integr8 * Putative homologues predictions for the above species. For more information see Homologue Selection at Integr8
Proper citation: CluSTr (RRID:SCR_007600) Copy
http://senselab.med.yale.edu/odordb
OdorDb is a database of odorant molecules, which can be searched in a few different ways. One can see odorant molecules in the OdorDB, and the olfactory receptors in ORDB that they experimentally shown to bind. You can search for odorant molecules based on their attributes or identities: Molecular Formula, Chemical Abstracts Service (CAS) Number and Chemical Class. Functional studies of olfactory receptors involve their interactions with odor molecules. OdorDB contains a list of odors that have been identified as binding to olfactory receptors.
Proper citation: Odor Molecules DataBase (RRID:SCR_007286) Copy
http://mips.gsf.de/genre/proj/ustilago/
The MIPS Ustilago maydis Genome Database aims to present information on the molecular structure and functional network of the entirely sequenced, filamentous fungus Ustilago maydis. The underlying sequence is the initial release of the high quality draft sequence of the Broad Institute. The goal of the MIPS database is to provide a comprehensive genome database in the Genome Research Environment in parallel with other fungal genomes to enable in depth fungal comparative analysis. The specific aims are to: 1. Generate and assemble Whole Genome Shotgun sequence reads yielding 10X coverage of the U. maydis genome 2. Integrate the genomic sequence assembly with physical maps generated by Bayer CropScience 3. Perform automated annotation of the sequence assembly 4. Align the strain 521 assembly with the FB1 assembly provided by Exelixis 5. Release the sequence assembly and results of our annotation and analysis to public Ustilago maydis is a basidiomycete fungal pathogen of maize and teosinte. The genome size is approximately 20 Mb. The fungus induces tumors on host plants and forms masses of diploid teliospores. These spores germinate and form haploid meiotic products that can be propagated in culture as yeast-like cells. Haploid strains of opposite mating type fuse and form a filamentous, dikaryotic cell type that invades plant tissue to reinitiate infection. Ustilago maydis is an important model system for studying pathogen-host interactions and has been studied for more than 100 years by plant pathologists. Molecular genetic research with U. maydis focuses on recombination, the role of mating in pathogenesis, and signaling pathways that influence virulence. Recently, the fungus has emerged as an excellent experimental model for the molecular genetic analysis of phytopathogenesis, particularly in the characterization of infection-specific morphogenesis in response to signals from host plants. Ustilago maydis also serves as an important model for other basidiomycete plant pathogens that are more difficult to work with in the laboratory, such as the rust and bunt fungi. Genomic sequence of U. maydis will also be valuable for comparative analysis of other fungal genomes, especially with respect to understanding the host range of fungal phytopathogens. The analysis of U. maydis would provide a framework for studying the hundreds of other Ustilago species that attack important crops, such as barley, wheat, sorghum, and sugarcane. Comparisons would also be possible with other basidiomycete fungi, such as the important human pathogen C. neoformans. Commercially, U. maydis is an excellent model for the discovery of antifungal drugs. In addition, maize tumors caused by U. maydis are prized in Hispanic cuisine and there is interest in improving commercial production. The complete putative gene set of the Broad Institute''s second release is loaded into the database and in addition all deviating putative genes from a putative gene set produced by MIPS with different gene prediction parameters are also loaded. The complete dataset will then be analysed, gene predictions will be manually corrected due to combined information derived from different gene prediction algorithms and, more important, protein and EST comparisons. Gene prediction will be restricted to ORFs larger than 50 codons; smaller ORFs will be included only if similarities to other proteins or EST matches confirm their existence or if a coding region was postulated by all prediction programs used. The resulting proteins will be annotated. They will be classified according to the MIPS classification catalogue receiving appropriate descriptions. All proteins with a known, characterized homolog will be automatically assigned to functional categories using the MIPS functional catalog. All extracted proteins are in addition automatically analysed and annotated by the PEDANT suite.
Proper citation: MIPS Ustilago maydis Database (RRID:SCR_007563) Copy
ChromDB is a chromatin database. Three types of sequences are included in the database: genomic-based (predominantly plant sequences); transcript-based (EST contigs or cDNAs for plants lacking a sequenced genome); and NCBI RefSeq sequences for a variety of model animal organisms. The Gene Record Page for any sequence indicates the type of sequence. The broad mission of ChromDB is display, annotate, and curate sequences of two broad functional classes of biologically important proteins: chromatin-associated proteins (CAPs) and RNA interference-associated proteins. Plant proteins are the major focus of the work support by The Plant Genome Research Program (PGRP) of the National Science Foundation. Our intent is to produce intensively curated sequence information and make it available to the research and teaching community in support of comparative analyses toward understanding the chromatin proteome in plants, especially in important crop species. In order to do a comparative analysis, it is necessary to include non-plant proteins in the database. Non-plant genes are not curated to the degree carried out for plants and to automate the process of data import, our non-plant genes are from the RefSeq database of NCBI. We reason that the inclusion of non-plant, model organisms will broaden the relevance and usefulness of ChromDB to the entire chromatin community and will provide a more complete data set for phylogenetic analyses in support of the evolution of the plant chromatin proteome. ChromDB is funded by a grant from the National Science Foundation Plant Genome Research Project(#DBI-0421679).
Proper citation: ChromDB- the chromatin database (RRID:SCR_007597) Copy
http://oxytricha.princeton.edu/dimorphism/database.htm
IES-MDS DB is a database of macronuclear and micronuclear genes in spirotrichous ciliates. The database contains information on 440 MDS pairs (each pair composed of the MIC and the MAC version of a given MDS), 392 IES and 361 pointer triples (each pointer has two active copies in the MIC and one copy in the MAC) (7). Out of the 440 MDSs, 235 are scrambled, and 65 are in the opposite strand in the MIC. A total of 320 IESs and 202 pointers are scrambled. For each pair of genes in the database the user can see the micronuclear and macronuclear organization and has the option to see all the MDS, IES and pointer sequences. Another option is to download the MIC sequence with the MDSs and pointers in uppercase and the IESs in lowercase. It is also possible to graphically compare the organization of several genes.
Proper citation: Ciliate IES-MDS database (RRID:SCR_007599) Copy
A database of general chemical information. The datasets are comprised of various available chemical datasets annotated with interesting properties to train and test machine-learning prediction and searching methods. Tools provided include ChemicalSearch, Virtual Chemical Space, Reaction Explorer, Datasets, and supplemental material. ChemicalSearch is a tool that allows users to find a chemical by basic criteria like molecular weight and predicted logP, or by the more abstract notion of structural similarity. Virtual Chemical Space is a tool which lets users interactively deconstruct target compounds into component precursors and reconstruct similar building-blocks into combinatorial libraries representing the virtual chemical space near the target compound. Reaction Explorer is a synthesis explorer and mechanism explorer. It provides an interactive system for learning and practicing reactions, syntheses and mechanisms in organic chemistry, with advanced support for the automatic generation of random problems, curved-arrow mechanism diagrams, and inquiry-based learning.
Proper citation: ChemDB: The UC Irvine ChemDB (RRID:SCR_007594) Copy
http://chicken.genomics.org.cn
ChickVD hosts high-quality sequence variation data, variation analysis in the context of chicken genes, cDNAs, chicken orthologs of human disease genes, genetic markers, quantitative trait loci (QTLs) etc . All data are uniquely mapped onto the RJF draft genome and graphically represented in MapView, an efficient visualization tool that allows users to browse sequence variations in the genomic and functional context. The sub-viewer TraceView assists users to view the vivid graphics of the original traces around the detected SNP. Users may query the data by the online search tool and define concrete limitations to extract records that are best suited to their research needs. For the convenience of data presentation in ChickVD, different types of sequence variations (substitutions, insertions or deletions) are all referred as ???SNPs''. ChickVD is updated constantly as more data generated and is under the continued improvement for its content and functionality
Proper citation: Chicken Variation Database (RRID:SCR_007595) Copy
A database to provide cleansed EST sequences of classified dbEST libraries. All dbEST libraries were classified according to organism, sequencing center, and eVOC ontologies (for human libraries). For each dbEST library, we provide three different EST sequences: raw, pre-cleansed, and user-cleansed. pre-cleansed ESTs are obtained from major contamination databases and cleaned of contaminated sequences. User-cleansed ESTs, however, involve the use of an automatic user-cleansing pipeline, in which sequences in a user-selected library are cleansed on-the-fly according to user-input options. CleanEST contains 62,008,259 EST sequences (24,000 libraries) with contamination information.
Proper citation: Cleansed EST Database (RRID:SCR_007587) Copy
http://www.copewithcytokines.org/cope.cgi
COPE is an encyclopedia of cytokines and has fully integrated subdictionaries on Angiogenesis, Apoptosis, Bacterial Modulins, CD Antigens, Cell lines, Eukaryotic cell types, Chemokines, CytokineTopics, Cytokine Concentrations in Body Fluids, Cytokine Inter-Species Reactivities, Dual identity proteins, Hematology, Innate Immunity Defense Proteins, Metalloproteinases, Protein domains, Regulatory peptide factors, Virokines, Viroceptors, and Virulence Factors. Most entries have a description as well as references.
Proper citation: COPE: Cytokines and Cells Online Pathfinder Encyclopaedia (RRID:SCR_007187) Copy
CATH is a hierarchical classification of protein domain structures, which clusters proteins at four major levels: Class (C), Architecture (A), Topology (T) and Homologous superfamily (H). The boundaries and assignments for each protein domain are determined using a combination of automated and manual procedures which include computational techniques, empirical and statistical evidence, literature review and expert analysis Users can search CATH by ID/Sequence/text. They can also browse CATH from the top of the hierarchy, or download CATH data.
Proper citation: CATH: Protein Structure Classification (RRID:SCR_007583) Copy
http://source.rcsb.org/jfatcatserver/ceHome.jsp
CE is a databases of alignments for all polypeptide chains. A representative set of proteins is available and kept current with the PDB, a method for calculating pairwise structure alignments. CE aligns two polypeptide chains using characteristics of their local geometry as defined by vectors between C alpha positions. Matches are termed aligned fragment pairs (AFPs). Heuristics are used in defining a set of optimal paths joining AFPs with gaps as needed. The path with the best RMSD is subject to dynamic programming to achieve an optimal alignment. For specific families of proteins additional characteristics are used to weight the alignment. Complete details are described in the paper (PDF format). Databases of alignments for all polypeptide chains and a representative set of proteins is available and kept current with the PDB
Proper citation: Combinatorial Extension (CE) (RRID:SCR_007585) Copy
The Biology WorkBench is a web-based tool for biologists. The WorkBench allows biologists to search many popular protein and nucleic acid sequence databases. Database searching is integrated with access to a wide variety of analysis and modeling tools, all within a point and click interface that eliminates file format compatibility problems. Register for a free account.
Proper citation: SDSC Biology Workbench (RRID:SCR_007188) Copy
CASRdb is a calcium-sensing receptor locus-specific database for mutations causing familial (benign) hypocalciuric hypercalcemia, neonatal severe hyperparathyroidism, and autosomal dominant hypocalcemia. The information can be searched by mutation, genotype-phenotype, clinical data, in vitro analyses, and authors of publications describing the mutations. CASRdb is regularly updated for new mutations and it also provides a mutation submission form to ensure up-to-date information. The home page of this database provides links to different web pages that are relevant to the CASR, as well as disease clinical pages, sequence of the CASR gene exons, and position of mutations in the CASR. The CASRdb will help researchers to better understand and analyze the mutations, and aid in structure-function analyses.
Proper citation: CASRDB- Calcium Sensing Receptor Database (RRID:SCR_007581) Copy
Can't find your Tool?
We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.
Welcome to the RRID Resources search. From here you can search through a compilation of resources used by RRID and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that RRID has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on RRID then you can log in from here to get additional features in RRID such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into RRID you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the sources that were queried against in your search that you can investigate further.
Here are the categories present within RRID that you can filter your data on
Here are the subcategories present within this category that you can filter your data on
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.
