Searching the RRID Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

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.

Search

Type in a keyword to search

On page 21 showing 401 ~ 420 out of 1,660 results
Snippet view Table view Download Top 1000 Results
Click the to add this resource to a Collection
  • RRID:SCR_003058

    This resource has 10+ mentions.

http://dire.dcode.org

Web server based on the Enhancer Identification (EI) method, to determine the chromosomal location and functional characteristics of distant regulatory elements (REs) in higher eukaryotic genomes. The server uses gene co-expression data, comparative genomics, and combinatorics of transcription factor binding sites (TFBSs) to find TFBS-association signatures that can be used for discriminating specific regulatory functions. DiRE's unique feature is the detection of REs outside of proximal promoter regions, as it takes advantage of the full gene locus to conduct the search. DiRE can predict common REs for any set of input genes for which the user has prior knowledge of co-expression, co-function, or other biologically meaningful grouping. The server predicts function-specific REs consisting of clusters of specifically-associated TFBSs, and it also scores the association of individual TFs with the biological function shared by the group of input genes. Its integration with the Array2BIO server allows users to start their analysis with raw microarray expression data.

Proper citation: Distant Regulatory Elements (RRID:SCR_003058) Copy   


http://mistdb.com

Database which contains the signal transduction proteins for complete and draft bacterial and archaeal genomes. The MiST2 database identifies and catalogs the repertoire of signal transduction proteins in microbial genomes.

Proper citation: MiST - Microbial Signal Transduction database (RRID:SCR_003166) Copy   


  • RRID:SCR_003735

    This resource has 50+ mentions.

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   


  • RRID:SCR_003496

    This resource has 10000+ mentions.

http://www.ncbi.nlm.nih.gov/RefSeq/

Collection of curated, non-redundant genomic DNA, transcript RNA, and protein sequences produced by NCBI. Provides a reference for genome annotation, gene identification and characterization, mutation and polymorphism analysis, expression studies, and comparative analyses. Accessed through the Nucleotide and Protein databases.

Proper citation: RefSeq (RRID:SCR_003496) Copy   


  • RRID:SCR_004173

    This resource has 10+ mentions.

http://www.inmex.ca./INMEX/

A web-based tool to support meta-analysis of multiple gene-expression data sets, as well as to enable integration of data sets from gene expression and metabolomics experiments. INMEX contains three functional modules. The data preparation module supports flexible data processing, annotation and visualization of individual data sets. The statistical analysis module allows researchers to combine multiple data sets based on P-values, effect sizes, rank orders and other features. The significant genes can be examined in functional analysis module for enriched Gene Ontology terms or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, or expression profile visualization. INMEX has built-in support for common gene/metabolite identifiers (IDs), as well as 45 popular microarray platforms for human, mouse and rat. Complex operations are performed through a user-friendly web interface in a step-by-step manner.

Proper citation: INMEX (RRID:SCR_004173) Copy   


  • RRID:SCR_003389

    This resource has 100+ mentions.

http://compbio.uthsc.edu/miRSNP/

Database of naturally occurring DNA variations in microRNA (miRNA) seed regions and miRNA target sites. MicroRNAs pair to the transcripts of protein-coding genes and cause translational repression or mRNA destabilization. SNPs and INDELs in miRNAs and their target sites may affect miRNA-mRNA interaction, and hence affect miRNA-mediated gene repression. The PolymiRTS database was created by scanning 3'UTRs of mRNAs in human and mouse for SNPs and INDELs in miRNA target sites. Then, the potential downstream effects of these polymorphisms on gene expression and higher-order phenotypes are identified. Specifically, genes containing PolymiRTSs, cis-acting expression QTLs, and physiological QTLs in mouse and the results of genome-wide association studies (GWAS) of human traits and diseases are linked in the database. The PolymiRTS database also includes polymorphisms in target sites that have been supported by a variety of experimental methods and polymorphisms in miRNA seed regions.

Proper citation: PolymiRTS (RRID:SCR_003389) Copy   


  • RRID:SCR_003331

    This resource has 100+ mentions.

http://www.phi-base.org/

Database that catalogs experimentally verified pathogenicity, virulence and effector genes from fungal, Oomycete and bacterial pathogens, which infect animal, plant, fungal and insect hosts. It is an invaluable resource in the discovery of genes in medically and agronomically important pathogens, which may be potential targets for chemical intervention. In collaboration with the FRAC team, it also includes antifungal compounds and their target genes. Each entry is curated by domain experts and is supported by strong experimental evidence (gene disruption experiments, STM etc), as well as literature references in which the original experiments are described. Each gene is presented with its nucleotide and deduced amino acid sequence, as well as a detailed description of the predicted protein's function during the host infection process. To facilitate data interoperability, genes have been annotated using controlled vocabularies and links to external sources (Gene Ontology terms, EC Numbers, NCBI taxonomy, EMBL, PubMed and FRAC).

Proper citation: PHI-base (RRID:SCR_003331) Copy   


  • RRID:SCR_003452

    This resource has 10+ mentions.

http://www.t-profiler.org

One of the key challenges in the analysis of gene expression data is how to relate the expression level of individual genes to the underlying transcriptional programs and cellular state. The T-profiler tool hosted on this website uses the t-test to score changes in the average activity of pre-defined groups of genes. The gene groups are defined based on Gene Ontology categorization, ChIP-chip experiments, upstream matches to a consensus transcription factor binding motif, and location on the same chromosome, respectively. If desired, an iterative procedure can be used to select a single, optimal representative from sets of overlapping gene groups. A jack-knife procedure is used to make calculations more robust against outliers. T-profiler makes it possible to interpret microarray data in a way that is both intuitive and statistically rigorous, without the need to combine experiments or choose parameters. Currently, gene expression data from Saccharomyces cerevisiae and Candida albicans are supported. Users can submit their microarray data for analysis by clicking on one of the two organism-specific tabs above. Platform: Online tool

Proper citation: T-profiler (RRID:SCR_003452) Copy   


  • RRID:SCR_004321

    This resource has 100+ mentions.

http://sideeffects.embl.de/

Database containing information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. The available information include side effect frequency, drug and side effect classifications as well as links to further information, for example drug-target relations. The SIDER Side Effect Resource represents an effort to aggregate dispersed public information on side effects. To our knowledge, no such resource exist in machine-readable form despite the importance of research on drugs and their effects. The creation of this resource was motivated by the many requests for data that we received related to our paper (Campillos, Kuhn et al., Science, 2008, 321(5886):263-6.) on the utilization of side effects for drug target prediction. Inclusion of side effects as readouts for drug treatment should have many applications and we hope to be able to enhance the respective research with this resource. You may browse the drugs by name, browse the side effects by name, download the current version of SIDER, or use the search interface.

Proper citation: SIDER (RRID:SCR_004321) Copy   


  • RRID:SCR_004477

    This resource has 10+ mentions.

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   


  • RRID:SCR_004353

    This resource has 10+ mentions.

https://reich.hms.harvard.edu/software

Software application that finds skews in ancestry that are potentially associated with disease genes in recently mixed populations like African Americans. It can be downloaded for either UNIX or Linux.

Proper citation: Ancestrymap (RRID:SCR_004353) Copy   


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   


https://cpndb.ca/

A curated collection of chaperonin sequence data collected from public databases or generated by a network of collaborators exploiting the cpn60 target in clinical, phylogenetic and microbial ecology studies. The database contains all available sequences for both group I and group II chaperonins. Users can search the database by Chaperonin type, group (I or II), BLAST, or other options, and can also enter and analyze FASTA sequences.

Proper citation: cpnDB: A Chaperonin Database (RRID:SCR_002263) Copy   


  • RRID:SCR_001503

    This resource has 100+ mentions.

http://toppcluster.cchmc.org/

A tool for performing multi-cluster gene functional enrichment analyses on large scale data (microarray experiments with many time-points, cell-types, tissue-types, etc.). It facilitates co-analysis of multiple gene lists and yields as output a rich functional map showing the shared and list-specific functional features. The output can be visualized in tabular, heatmap or network formats using built-in options as well as third-party software. It uses the hypergeometric test to obtain functional enrichment achieved via the gene list enrichment analysis option available in ToppGene.

Proper citation: ToppCluster (RRID:SCR_001503) Copy   


  • RRID:SCR_001892

    This resource has 1+ mentions.

http://statalign.github.io/

Software package for Bayesian analysis of protein, DNA and RNA sequences. It utilizes multiple alignments, phylogenetic trees and evolutionary parameters to quantify uncertainty in these analyses. It is written in Java.

Proper citation: StatAlign (RRID:SCR_001892) Copy   


  • RRID:SCR_001767

    This resource has 1+ mentions.

http://www.nactem.ac.uk/facta/

Text mining tool to discover associations between biomedical concepts from MEDLINE articles. Use the service from your browser or via a Web Service. The whole MEDLINE corpus containing more than 20 million articles is indexed with an efficient text search engine, and it allows you to navigate such associations and their textual evidence in a highly interactive manner - the system accepts arbitrary query terms and displays relevant concepts immediately. A broad range of important biomedical concepts are covered by the combination of a machine learning-based term recognizer and large-scale dictionaries for genes, proteins, diseases, and chemical compounds. There is also a FACTA+ visualization service that can be found here: http://www.nactem.ac.uk/facta-visualizer/

Proper citation: FACTA+. (RRID:SCR_001767) Copy   


  • RRID:SCR_002178

    This resource has 100+ mentions.

https://www.biodiscovery.com/search/node?keys=Imagene

Software tool as convolutional neural network to quantify natural selection from genomic data.Supervised machine learning algorithm to predict natural selection and estimate selection coefficients from population genomic data. Can be used to estimate any parameter of interest from evolutionary population genetics model., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ImaGene (RRID:SCR_002178) Copy   


  • RRID:SCR_000060

    This resource has 1+ mentions.

https://github.com/ndaniel/fusioncatcher

Software that searches for novel/known fusion genes, translocations, and chimeras in RNA-seq data (paired-end reads from Illumina NGS platforms like Solexa and HiSeq) from diseased samples.

Proper citation: FusionCatcher (RRID:SCR_000060) Copy   


  • RRID:SCR_000058

http://dissect-trans.sourceforge.net/Home

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software transcriptome-to-genome alignment tool, which can identify and characterize transcriptomic events such as duplications, inversions, rearrangements and fusions.

Proper citation: Dissect (RRID:SCR_000058) Copy   


  • RRID:SCR_005096

    This resource has 500+ mentions.

http://soybase.org

Professionally curated repository for genetics, genomics and related data resources for soybean that contains the most current genetic, physical and genomic sequence maps integrated with qualitative and quantitative traits. SoyBase includes annotated Williams 82 genomic sequence and associated data mining tools. The genetic and sequence views of the soybean chromosomes and the extensive data on traits and phenotypes are extensively interlinked. This allows entry to the database using almost any kind of available information, such as genetic map symbols, soybean gene names or phenotypic traits. The repository maintains controlled vocabularies for soybean growth, development, and traits that are linked to more general plant ontologies. Contributions to SoyBase or the Breeder''s Toolbox are welcome.

Proper citation: SoyBase (RRID:SCR_005096) 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.

Can't find the RRID you're searching for? X
  1. RRID Portal Resources

    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.

  2. Navigation

    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.

  3. Logging in and Registering

    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.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Save Your Search

    You can save any searches you perform for quick access to later from here.

  6. Query Expansion

    We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.

  7. Collections

    If you are logged into RRID you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  8. Sources

    Here are the sources that were queried against in your search that you can investigate further.

  9. Categories

    Here are the categories present within RRID that you can filter your data on

  10. Subcategories

    Here are the subcategories present within this category that you can filter your data on

  11. Further Questions

    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.

X