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
X
Forgot Password

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

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 5 showing 81 ~ 100 out of 997 results
Snippet view Table view Download 997 Result(s)
Click the to add this resource to a Collection

https://bams1.org/

Knowledge management system designed to handle neurobiological information at different levels of organization of vertebrate nervous system. Database and repository for information about neural circuitry, storing and analyzing data concerned with nomenclature, taxonomy, axonal connections, and neuronal cell types. Handles data and metadata collated from original literature, or inserted by scientists that is associated to four levels of organization of vertebrate nervous system. Data about expressed molecules, neuron types and classes, brain regions, and networks of brain regions.

Proper citation: Brain Architecture Management System (RRID:SCR_007251) Copy   


  • RRID:SCR_007248

    This resource has 1+ mentions.

http://cardiogenomica.altervista.org/CARDIOGENOMICS/CardioGenomics%20Homepage.htm

The primary goal of the CardioGenomics PGA is to begin to link genes to structure, function, dysfunction and structural abnormalities of the cardiovascular system caused by clinically relevant genetic and environmental stimuli. The principal biological theme to be pursued is how the transcriptional network of the cardiovascular system responds to genetic and environmental stresses to maintain normal function and structure, and how this network is altered in disease. This PGA will generate a high quality, comprehensive data set for the functional genomics of structural and functional adaptation of the cardiovascular system by integrating expression data from animal models and human tissue samples, mutation screening of candidate genes in patients, and DNA polymorphisms in a well characterized general population. Such a data set will serve as a benchmark for future basic, clinical, and pharmacogenomic studies. Training and education are also a key focus of the CardioGenomics PGA. In addition to ongoing journal clubs and seminars, the PGA will be sponsoring symposia at major conferences, and developing workshops related to the areas of focus of this PGA. Information regarding upcoming events can be found in the Events section of this site, and information about training and education opportunities sponsored by CardioGenomics can be found on the Teaching and Education page. The CardioGenomics project came to a close in 2005. This server, cardiogenomics.med.harvard.edu, remains online in order to continue to distribute data that was generated by investigators under the auspices of the CardioGenomics Program for Genomic Applications (PGA). :Sponsors: This resource is supported by The National Heart, Lung and Blood Institute (NHLBI) of the NIH., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CardioGenomics (RRID:SCR_007248) Copy   


  • RRID:SCR_008132

    This resource has 100+ mentions.

https://www.ncbi.nlm.nih.gov/genbank/dbest/

Database as a division of GenBank that contains sequence data and other information on single-pass cDNA sequences, or Expressed Sequence Tags, from a number of organisms.

Proper citation: dbEST (RRID:SCR_008132) Copy   


  • RRID:SCR_008034

    This resource has 1+ mentions.

http://wwwmgs.bionet.nsc.ru/mgs/gnw/about.shtml

GeneNetWorks is designed for accumulation of experimental data, data navigation, data analysis, and analysis of dependencies in the field of gene expression regulation. It integrates the databases and programs for processing the data about structure and function of DNA, RNA, and proteins, together with the other information resources important for gene expression description. The unique property of above described system is that all the resources within the system GeneNetWorks are divided according to the natural hierarchy of molecular genetic systems and has the following levels: (1) DNA; (2) RNA; (3) proteins; and (4) gene networks. Each module contains: 1) experimental data represented as a database or some sample; 2) program for data analysis; 3) results of an automated data processing; 4) tools for the graphical representation of these data and the results of the data analyses.

Proper citation: GeneNetWorks (RRID:SCR_008034) Copy   


http://www.genomatix.de/

Genomatix is a privately held company that offers software, databases, and services aimed at understanding gene regulation at the molecular level representing a central part of systems biology. Its multilayer integrative approach is a working implementation of systems biology principles. Genomatix combines sequence analysis, functional promoter analysis, proprietary genome annotation, promoter sequence databases, comparative genomics, scientific literature data mining, pathway databases, biological network databases, pathway analysis, network analysis, and expression profiling into working solutions and pipelines. It also enables better understanding of biological mechanisms under different conditions and stimuli in the biological context of your data. Some of Genomatix'' most valuable assets are the strong scientific background and the years of experience in research & discovery as well as in development & application of scientific software. Their firsthand knowledge of all the complexities involved in the in-silico analysis of biological data makes them a first-rate partner for all scientific projects involving the evaluation of gene regulatory mechanisms. The Genomatix team has more than a decade of scientific expertise in the successful application of computer aided analysis of gene regulatory networks, which is reflected by more than 150 peer reviewed scientific publications from Genomatix'' scientists More than 35,000 researchers in industry and academia around the world use this technology. The software available in Genomatix are: - GenomatixSuite: GenomatixSuite is our comprehensive software bundle including ElDorado, Gene2Promoter, GEMS Launcher, MatInspector and MatBase. GenomatixSuite PE also includes BiblioSphere Pathway Edition. Chromatin IP Software - RegionMiner: Fast, extensive analysis of genomic regions. - ChipInspector: Discover the real power of your microarray data. Genome Annotation Software - ElDorado: Extended Genome Annotation. - Gene2Promoter: Retrieve & analyze promoters - GPD: The Genomatix Promoter Database, which is now included with Gene2Promoter. Knowledge Mining Software - BiblioSpere : The next level of pathway/genomics analysis. - LitInspector: Literature and pathway analysis for free. Sequence Analysis Software - GEMS Launcher: Our integrated collection of sequence analysis tools. - MalInspector: Search transcription factor binding sites - MatBase: The transcription factor knowledge base. Other (no registration required) Software - DiAlign: Multiple alignment of DNA/protein sequence. - Genomatix tools: Various small tools for sequence statistics, extraction, formatting, etc.

Proper citation: Genomatix Software: Understanding Gene Regulation (RRID:SCR_008036) Copy   


http://mialab.mrn.org/index.html

MIALAB, headed by Dr. Vince Calhoun, focuses on developing and optimizing methods and software for quantitative analysis of structure and function in medical images with particular focus on the study of psychiatric illness. We work with many types of data, including functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), electroencephalography (EEG), structural imaging and genetic data. Much of our time is spent working on new methods for flexible analysis of brain imaging data. The use of data driven approaches is very useful for extracting potentially unpredictable patterns within these data. However such methods can be further improved by incorporating additional prior information as constraints, in order to benefit from what we know. To this end, we draw heavily from the areas of image processing, adaptive signal processing, estimation theory, neural networks, statistical signal processing, and pattern recognition.

Proper citation: MIALAB - Medical Image Analysis Lab (RRID:SCR_006089) Copy   


  • RRID:SCR_006234

    This resource has 10+ mentions.

https://proteomecommons.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A public resource for sharing general proteomics information including data (Tranche repository), tools, and news. Joining or creating a group/project provides tools and standards for collaboration, project management, data annotation, permissions, permanent storage, and publication.

Proper citation: Proteome Commons (RRID:SCR_006234) Copy   


  • RRID:SCR_006360

    This resource has 1000+ mentions.

http://www.chemspider.com/

Collection of chemical structures. Provides access to structures, properties and associated information from hundreds of data sources to find compounds of interest and provides services to improve this data by curation and annotation and to integrate it with users applications.

Proper citation: ChemSpider (RRID:SCR_006360) Copy   


  • RRID:SCR_006542

    This resource has 50+ mentions.

https://repository.niddk.nih.gov/home/

NIDDK Central Repositories are two separate contract funded components that work together to store data and samples from significant, NIDDK funded studies. First component is Biorepository that gathers, stores, and distributes biological samples from studies. Biorepository works with investigators in new and ongoing studies as realtime storage facility for archival samples.Second component is Data Repository that gathers, stores and distributes incremental or finished datasets from NIDDK funded studies Data Repository helps active data coordinating centers prepare databases and incremental datasets for archiving and for carrying out restricted queries of stored databases. Data Repository serves as Data Coordinating Center and website manager for NIDDK Central Repositories website.

Proper citation: NIDDK Central Repository (RRID:SCR_006542) Copy   


  • RRID:SCR_006620

    This resource has 1+ mentions.

http://edamontology.org/

An ontology of bioinformatics operations (tool, application, or workflow functions), types of data including identifiers, topics (application domains), and data formats. The applications of EDAM are within organizing tools and data, finding suitable tools in catalogues, and integrating them into complex applications or workflows. Semantic annotations with EDAM are applicable to diverse entities such as for example Web services, databases, programmatic libraries, standalone tools and toolkits, interactive applications, data schemas, data sets, or publications within bioinformatics. Annotation with EDAM may also contribute to data provenance, and EDAM terms and synonyms can be used in text mining. EDAM - and in particular the EDAM Data sub-ontology - serves also as a markup vocabulary for bioinformatics data on the Semantic Web.

Proper citation: EDAM Ontology (RRID:SCR_006620) Copy   


http://www.ars-grin.gov/

Web server to provide germplasm information about plants, animals, microbes, invertebrates and access to databases that maintain passport, characterization, evaluation, inventory, and distribution data for the management and utilization of national germplasm collections. Under control of the U.S. Department of Agriculture's Agricultural Research Service to support the National Genetic Resources Program (NGRP). Operated by the Database Management Unit of the National Germplasm Resource Laboratory in Beltsville, Maryland.

Proper citation: Germplasm Resources Information Network (RRID:SCR_006675) Copy   


http://dash.harvard.edu/

Harvard University''s central service for sharing and preserving work. In addition to the scholarly journal articles targeted by Harvard''s several open access resolutions, DASH maybe used to self-archive manuscripts and materials. DASH supports a variety of file formats, and users are encouraged to deposit related materials with manuscripts (including data, images, audio and video files, etc.) When users deposit their work in DASH, it becomes visible to colleagues around the world by virtue of metadata harvesting, Google Scholar, and other indexing services. Higher visibility leads to higher rates of citation and impact. When users post early versions of their work, before publication, they establish intellectual priority sooner. Users act in their own best interests by taking part in the University''s mission to share and preserve the knowledge produced there. Because Harvard now has a prior, non-exclusive license to faculty journal articles in schools with open access policies, those faculty members are required to act accordingly when publishing journal articles, either by attaching an addendum to their publication agreement or obtaining a waiver. They then must deposit the publication in DASH.

Proper citation: Digital Access to Scholarship at Harvard (RRID:SCR_004122) Copy   


  • RRID:SCR_010471

    This resource has 10+ mentions.

http://databrary.org/

Project aims to promote data sharing, archiving, and reuse among researchers who study human development. Focuses on creating tools for scientists to store, manage, preserve, analyze and share video and related data.

Proper citation: Databrary (RRID:SCR_010471) Copy   


  • RRID:SCR_010881

    This resource has 5000+ mentions.

http://homer.ucsd.edu/

Software tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.

Proper citation: HOMER (RRID:SCR_010881) Copy   


  • RRID:SCR_010970

    This resource has 1+ mentions.

http://www.arrayserver.com/wiki/index.php?title=ArrayStudio_Online_Help

Software package which provides statistics and visualization for analysis of high dimensional quantification data including microarray or RTPCR data or Taqman data, genotype data including SNP or Copy Number data and Next Generation Sequencing data. Provides integrated environment for analyzing and visualizing high dimensional data.

Proper citation: Array Studio (RRID:SCR_010970) Copy   


  • RRID:SCR_010943

    This resource has 10000+ mentions.

http://bioinf.wehi.edu.au/limma/

Software package for the analysis of gene expression microarray data, especially the use of linear models for analyzing designed experiments and the assessment of differential expression.

Proper citation: LIMMA (RRID:SCR_010943) Copy   


  • RRID:SCR_011323

    This resource has 5000+ mentions.

http://www.moleculardevices.com/products/software/pclamp.html

Software suite for electrophysiology data acquisition and analysis by Molecular Devices. Used for the control and recording of voltage clamp, current clamp, and patch clamp experiments. The software suite consists of Clampex 11 Software for data acquisition, AxoScope 11 Software for background recording, Clampfit 11 Software for data analysis, and optional Clampfit Advanced Analysis Module for sophisticated and streamlined analysis.

Proper citation: pClamp (RRID:SCR_011323) Copy   


  • RRID:SCR_011843

    This resource has 100+ mentions.

https://github.com/najoshi/sabre

Software tool to demultiplex barcoded reads into separate files. Works on both single-end and paired-end data in fastq format. Used in next generation sequencing to analyze a broad range of data.

Proper citation: sabre (RRID:SCR_011843) Copy   


  • RRID:SCR_012835

    This resource has 1000+ mentions.

http://www.bioconductor.org/packages/release/bioc/html/affy.html

Software R package of functions and classes for the analysis of oligonucleotide arrays manufactured by Affymetrix. Used to process probe level data and for exploratory oligonucleotide array analysis.

Proper citation: affy (RRID:SCR_012835) Copy   


  • RRID:SCR_012802

    This resource has 10000+ mentions.

http://bioconductor.org/packages/edgeR/

Bioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.

Proper citation: edgeR (RRID:SCR_012802) 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