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.
Web based integrative platform for transcriptional regulation studies.
Proper citation: Cistrome (RRID:SCR_000242) Copy
https://github.com/macs3-project/MACS
Software Python package for identifying transcript factor binding sites. Used to evaluate significance of enriched ChIP regions. Improves spatial resolution of binding sites through combining information of both sequencing tag position and orientation. Can be used for ChIP-Seq data alone, or with control sample with increase of specificity.
Proper citation: MACS (RRID:SCR_013291) Copy
http://www.metabolomicsworkbench.org
Repository for metabolomics data and metadata which provides analysis tools and access to various resources. NIH grantees may upload data and general users can search metabolomics database. Provides protocols for sample preparation and analysis, information about NIH Metabolomics Program, data sharing guidelines, funding opportunities, services offered by its Regional Comprehensive Metabolomics Resource Cores (RCMRC)s, and training workshops.
Proper citation: Metabolomics Workbench (RRID:SCR_013794) Copy
https://bitbucket.org/biobakery/biobakery/wiki/Home
Analysis environment and collection of individual software tools to process raw shotgun metagenome or metatranscriptome sequencing data for quantitative microbial community profiling. Used for a metaomics data analysis., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: biobakery (RRID:SCR_016596) Copy
https://pachterlab.github.io/sleuth/about
Software tool for analysis of RNA-Seq experiments for which transcript abundances have been quantified with kallisto. Used for the differential analysis of gene expression data that utilizes bootstrapping in conjunction with response error linear modeling to decouple biological variance from inferential variance.
Proper citation: sleuth (RRID:SCR_016883) Copy
http://amp.pharm.mssm.edu/X2K/
Software tool to produce inferred networks of transcription factors, proteins, and kinases predicted to regulate the expression of the inputted gene list by combining transcription factor enrichment analysis, protein-protein interaction network expansion, with kinase enrichment analysis. It provides the results as tables and interactive vector graphic figures.
Proper citation: eXpression2Kinases (RRID:SCR_016307) Copy
Web multi omics knowledgebase based upon public, manually curated transcriptomic and cistromic datasets involving genetic and small molecule manipulations of cellular receptors, enzymes and transcription factors. Integrated omics knowledgebase for mammalian cellular signaling pathways. Web browser interface was designed to accommodate numerous routine data mining strategies. Datasets are biocurated versions of publically archived datasets and are formatted according to recommendations of the FORCE11 Joint Declaration on Data Citation Principles73, and are made available under Creative Commons CC 3.0 BY license. Original datasets are available.
Proper citation: Signaling Pathways Project (RRID:SCR_018412) Copy
ToppGene Suite is a one-stop portal for gene list enrichment analysis and candidate gene prioritization based on functional annotations and protein interactions network. ToppGene Suite is a one-stop portal for (i) gene list functional enrichment, (ii) candidate gene prioritization using either functional annotations or network analysis and (iii) identification and prioritization of novel disease candidate genes in the interactome. Functional annotation-based disease candidate gene prioritization uses a fuzzy-based similarity measure to compute the similarity between any two genes based on semantic annotations. The similarity scores from individual features are combined into an overall score using statistical meta-analysis.
Proper citation: ToppGene Suite (RRID:SCR_005726) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 26,2019. In October 2016, T1DBase has merged with its sister site ImmunoBase (https://immunobase.org). Documented on March 2020, ImmunoBase ownership has been transferred to Open Targets (https://www.opentargets.org). Results for all studies can be explored using Open Targets Genetics (https://genetics.opentargets.org). Database focused on genetics and genomics of type 1 diabetes susceptibility providing a curated and integrated set of datasets and tools, across multiple species, to support and promote research in this area. The current data scope includes annotated genomic sequences for suspected T1D susceptibility regions; genetic data; microarray data; and global datasets, generally from the literature, that are useful for genetics and systems biology studies. The site also includes software tools for analyzing the data.
Proper citation: T1DBase (RRID:SCR_007959) Copy
http://bioplex.hms.harvard.edu/
Database of cell lines with each expressing a tagged version of a protein from the ORFeome collection. The overarching project goal is to determine protein interactions for every member of the collection.
Proper citation: BioPlex (RRID:SCR_016144) Copy
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
http://bioconductor.org/packages/CATALYST/
Software R package to provide pipeline for preprocessing of cytometry data, including normalization using bead standards, single cell deconvolution, and bead based compensation.
Proper citation: CATALYST (RRID:SCR_017127) 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 NIF Resources search. From here you can search through a compilation of resources used by NIF and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that NIF 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 NIF then you can log in from here to get additional features in NIF 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 NIF 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 NIF 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.
Welcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
