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.
Supplier of mice for research purposes.
Proper citation: Taconic Biosciences (RRID:SCR_016410) Copy
https://ihg.helmholtz-muenchen.de/cgi-bin/hw/hwa1.pl
Software tool for performing tests for deviation from Hardy-Weinberg equilibrium and tests for association. Used in population-based genetic association studies to identify susceptibility genes for complex diseases.
Proper citation: Tests for deviation from Hardy-Weinberg equilibrium (RRID:SCR_016496) Copy
http://homer.ucsd.edu/homer/microarray/index.html
Software tool to analyze the promoters of genes and look for motifs that are enriched in the target gene promoters relative to other promoters. Used for gene based analysis to provide a list of genes that should contain the same elements, such as genes that are co-regulated. It includes gene ontology analysis and can be used to look for RNA motifs in mRNAs.
Proper citation: findMotif.pl (RRID:SCR_016417) Copy
http://amp.pharm.mssm.edu/DGB/
Web based application to assist researchers with identifying drugs and small molecules that are predicted to maximally influence expression of mammalian gene of interest. Used to identify drugs and small molecules to regulate expression of target genes for research purpose only. Application for ranking drugs to modulate specific gene based on transcriptomic signatures.
Proper citation: Drug Gene Budger (RRID:SCR_016489) Copy
https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000363.v16.p10
Project to generate extensive biomarker data from Framingham Heart Study participants using immunoassays, proteomics, metabolomics/lipomics, and gene expression and microRNA profiling to advance personalized medicine through biomarker discovery and validation.
Proper citation: SABRe CVD Initiative (RRID:SCR_016572) Copy
https://github.com/WGS-TB/MentaLiST
Software for a MLST (multi-locus sequence typing) caller, based on a k-mer counting algorithm and written in the Julia language. Designed and implemented to handle large typing schemes.
Proper citation: MentaLiST (RRID:SCR_016469) Copy
https://github.com/umerijaz/nanopore
Software for a workflow for amplicon sequencing from mixed microbial communities on the nanopore sequencing platform. Used for full-length SSU rRNA gene sequencing.
Proper citation: NanoAmpli-Seq (RRID:SCR_016710) Copy
https://github.com/iychoi/libra
Hadoop based tool for massive comparative metagenomics analysis. Compute the similarity between metagenomic samples.
Proper citation: Libra (RRID:SCR_016608) Copy
Web tool to import raw cDNA sequences, clean sequences, build sequence contigs, perform SignalP analysis, BLAST contigs against numerous BLAST databases, and view the results. Automates large scale cDNA sequence analysis., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: dCAS (RRID:SCR_016612) Copy
https://www.stemformatics.org/#
Gene expression data portal developed for stem cell community, containing public gene expression datasets derived from microarray, RNA sequencing and single cell profiling technologies. Portal to visualize and download curated stem cell data. Provides easy to use and intuitive tools for biologists to visually explore data, including interactive gene expression profiles, principal component analysis plots and hierarchical clusters, among others.
Proper citation: Stemformatics (RRID:SCR_017002) Copy
http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html
Software R package for statistical analysis and visualization of functional profiles for genes and gene clusters.
Proper citation: clusterProfiler (RRID:SCR_016884) Copy
https://picrust.github.io/picrust/
Software package to predict metagenome functional content from marker gene (e.g., 16S rRNA) surveys and full genomes. Used to predict which gene families are present and then combines gene families to estimate the composite metagenome.
Proper citation: PICRUSt (RRID:SCR_016855) Copy
http://www.osc.riken.jp/english/
Omics Science Center is aiming to develop a comprehensive system called Life Science Accelerator(LSA) for the advancement of omics research. The LSA is a comprehensive system consists of biological resources, human resources, technologies, know-how, and essential administrative ability. Ultimate goal of LSA is to support and accelerate the advancement in life science research. Omics is the comprehensive study of molecules in living organisms. The complete sequencing of genomes (the complete set of genes in an organism) has enabled rapid developments in the collection and analysis of various types of comprehensive molecular data such as transcriptomes (the complete set of gene expression data) and proteomes (the complete set of intracellular proteins). Fundamental omics research aims to link these omics data to molecular networks and pathways in order to advance the understanding of biological phenomena as systems at the molecular level.
Proper citation: RIKEN Omics Science Center (RRID:SCR_008241) Copy
http://www.repairgenes.org/index.shtml
The aim of the repairGenes site is to be a source of information about DNA repair genes and a useful resource for research on DNA repair. At the moment, the site contains information about a number of DNA repair genes from a set of selected species. The information is organized by organism and by biological process term as defined by the Gene Ontology (GO) project. The coverage of DNA repair genes is not complete, but hopefully it satisfies to demonstrate the concept and generate ideas for future versions of the system. At present, the raw data about DNA repair genes is extracted from the SWISS-PROT database, and categorized using the GO system. SWISS-PROT entries are being annotated by the Gene Ontology Annotation project at EBI. GOA is an ongoing project which will become more complete with time. As more data is released, this will be fed into repairGenes to keep it up-to-date. In future versions, the user will be able to search freely among organisms and categories of repair genes, enabling easy comparisons between species. For a taste of this, please have a look at the overview of repair genes from five major organisms. The amount of information in the system will be increased and the quality will be improved in the future. So will the features of the system.
Proper citation: repairGenes (RRID:SCR_008240) Copy
http://bioinf.uni-greifswald.de/augustus/
Software for gene prediction in eukaryotic genomic sequences. Serves as a basis for further steps in the analysis of sequenced and assembled eukaryotic genomes.
Proper citation: Augustus (RRID:SCR_008417) Copy
http://www.nature.com/nature/supplements/collections/
This website provides summary collections written for a broad audience highlighting some of the significant advances in a particular field. These are not scientific articles although they may reference scientific work. Sponsors: This resource is supported by Nature.com
Proper citation: Nature Supplements: Collections archive (RRID:SCR_008337) Copy
https://www.stat.auckland.ac.nz/~paul/plaudits/Iobion.htm
GeneTraffic is a web-based microarray data analysis and management software developed by Iobion Informatics that allows users to log onto a server, upload their microarray data and perform analysis and project management remotely. GeneTraffic was made by Iobion Informatics (now under Stratagene) and can be accessed thorough Internet Explorer 6.0 or greater on Windows XP.
Proper citation: GeneTraffic (RRID:SCR_008651) Copy
http://crezoo.crt-dresden.de/crezoo/
Database of helpful set of CreERT2 driver lines expressing in various regions of the developing and adult zebrafish. The lines have been generated via the insertion of a mCherry-T2A-CreERT2 in a gene trap approach or by using promoter fragments driving CreERT2. You can search the list of all transgenic lines or single entries by insertions (gene) or expression patterns (anatomy/region). In most cases the CreERT2 expression profile using in situ hybridization at 24 hpf and 48 hpf is shown, but also additional information (e.g. mCherry or CreERT2 expression at adult stages, transactivation of a Cre-dependent reporter line) is displayed. Currently, not all insertions have been mapped to a genomic location but the database will be regularly updated adding newly generated insertions and mapping information. Your help in improving and broadening the database by giving your opinion or knowledge of expression patterns is highly appreciated.
Proper citation: CreZoo (RRID:SCR_008919) Copy
http://go.princeton.edu/cgi-bin/GOTermFinder
The Generic GO Term Finder finds the significant GO terms shared among a list of genes from an organism, displaying the results in a table and as a graph (showing the terms and their ancestry). The user may optionally provide background information or a custom gene association file or filter evidence codes. This tool is capable of batch processing multiple queries at once. GO::TermFinder comprises a set of object-oriented Perl modules GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script. This implementation, developed at the Lewis-Sigler Institute at Princeton, depends on the GO-TermFinder software written by Gavin Sherlock and Shuai Weng at Stanford University and the GO:View module written by Shuai Weng. It is made publicly available through the GMOD project. The full source code and documentation for GO:TermFinder are freely available from http://search.cpan.org/dist/GO-TermFinder/. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: Generic GO Term Finder (RRID:SCR_008870) Copy
APID Interactomes (Agile Protein Interactomes DataServer) provides information on the protein interactomes of numerous organisms, based on the integration of known experimentally validated protein-protein physical interactions (PPIs). The interactome data includes a report on quality levels and coverage over the proteomes for each organism included. APID integrates PPIs from primary databases of molecular interactions (BIND, BioGRID, DIP, HPRD, IntAct, MINT) and also from experimentally resolved 3D structures (PDB) where more than two distinct proteins have been identified. This collection references protein interactors, through a UniProt identifier.
Proper citation: Agile Protein Interactomes DataServer (RRID:SCR_008871) 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.