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.
http://oncowiki.info/index.php?title=Main_Page
A free repository for oncology information, chemotherapy protocols, and cancer treatment regimens. It is meant for Healthcare providers working in the field of Oncology.
Proper citation: Onco Wiki (RRID:SCR_005002) Copy
DDMoRe project to develop common standards and tools to allow scientists to share their models. Developed model repository which enables access to curated and shared knowledge for benefit of model informed drug discovery.
Proper citation: DDMoRe (RRID:SCR_003851) Copy
Database enables integration of genomic and phenomic data by providing access to primary experimental data, data collection protocols and analysis tools. Data represent behavioral, morphological and physiological disease-related characteristics in naive mice and those exposed to drugs, environmental agents or other treatments. Collaborative standardized collection of measured data on laboratory mouse strains to characterize them in order to facilitate translational discoveries and to assist in selection of strains for experimental studies. Includes baseline phenotype data sets as well as studies of drug, diet, disease and aging effect., protocols, projects and publications, and SNP, variation and gene expression studies. Provides tools for online analysis. Data sets are voluntarily contributed by researchers from variety of institutions and settings, or retrieved by MPD staff from open public sources. MPD has three major types of strain-centric data sets: phenotype strain surveys, SNP and variation data, and gene expression strain surveys. MPD collects data on classical inbred strains as well as any fixed-genotype strains and derivatives that are openly acquirable by the research community. New panels include Collaborative Cross (CC) lines and Diversity Outbred (DO) populations. Phenotype data include measurements of behavior, hematology, bone mineral density, cholesterol levels, endocrine function, aging processes, addiction, neurosensory functions, and other biomedically relevant areas. Genotype data are primarily in the form of single-nucleotide polymorphisms (SNPs). MPD curates data into a common framework by standardizing mouse strain nomenclature, standardizing units (SI where feasible), evaluating data (completeness, statistical power, quality), categorizing phenotype data and linking to ontologies, conforming to internal style guides for titles, tags, and descriptions, and creating comprehensive protocol documentation including environmental parameters of the test animals. These elements are critical for experimental reproducibility.
Proper citation: Mouse Phenome Database (MPD) (RRID:SCR_003212) Copy
http://www.animalgenome.org/cgi-bin/QTLdb/index
Database of trait mapping data, i.e. QTL (phenotype / expression, eQTL), candidate gene and association data (GWAS) and copy number variations (CNV) mapped to livestock animal genomes, to facilitate locating and comparing discoveries within and between species. New data and database tools are continually developed to align various trait mapping data to map-based genome features, such as annotated genes. QTLdb is open to house QTL/association date from other animal species where feasible. Most scientific journals require that any original QTL/association data be deposited into public databases before paper may be accepted for publication. User curator accounts are provided for direct data deposit. Users can download QTLdb data from each species or individual chromosome.
Proper citation: Animal QTLdb (RRID:SCR_001748) Copy
Interdisciplinary data platform provides access to research data and information from all fields of applied plasma physics and plasma medicine. Aims at distributing, publishing and archiving of data and information, supporting findability, accessibility, interoperability and re-use of data, for low temperature plasma physics community.Most of data are freely available and can be used under terms of license listed on dataset description page. Each dataset can be identified, cited and shared by using Digital Object Identifier.
Proper citation: INPTDAT (RRID:SCR_022167) Copy
Paleoecology database for plio-pleistocene to holocene fossil data with a centralized structure for interdisciplinary, multiproxy analyses and common tool development; discipline-specific data can also be easily accessed. Data currently include North American Pollen (NAPD) and fossil mammals (FAUNMAP). Other proxies (plant macrofossils, beetles, ostracodes, diatoms, etc.) and geographic areas (Europe, Latin America, etc.) will be added in the near future. Data are derived from sites from the last 5 million years.
Proper citation: Neotoma Paleoecology Database (RRID:SCR_002190) Copy
Accepts and provides access to biogeographic data collected throughout the global oceans. The datasets are integrated so you can search them all seamlessly by species name, higher taxonomic level, geographic area, depth, and time; and then map and find environmental data related to the locations. Created by the Census of Marine Life, OBIS is now part of the Intergovernmental Oceanographic Commission (IOC) of UNESCO, under its International Oceanographic Data and Information Exchange (IODE) programme
Proper citation: OBIS (RRID:SCR_006933) Copy
https://neuroscienceblueprint.nih.gov/Resources-Tools/Blueprint-Resources-Tools-Library
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 22, 2023. National initiative to advance biomedical research through data sharing and online collaboration that provides data sharing infrastructure, software tools, strategies and advisory services. Groups may choose whether to share data internally or with external audiences. Hardware and data remain under control of individual user groups.
Proper citation: Biomedical Informatics Research Network (RRID:SCR_005163) Copy
http://connectomics.org/viewer
Extensible, scriptable, pythonic software tool for visualization and analysis in structural neuroimaging research on many spatial scales. Employing the Connectome File Format, diverse data such as networks, surfaces, volumes, tracks and metadata are handled and integrated. The field of Connectomics research benefits from recent advances in structural neuroimaging technologies on all spatial scales. The need for software tools to visualize and analyze the emerging data is urgent. The ConnectomeViewer application was developed to meet the needs of basic and clinical neuroscientists, as well as complex network scientists, providing an integrative, extensible platform to visualize and analyze Connectomics data. With the Connectome File Format, interlinking different datatypes such as hierarchical networks, surface data, volumetric data is easy and might provide new ways of analyzing and interacting with data. Furthermore, ConnectomeViewer readily integrates with: * ConnectomeWiki: a semantic knowledge base representing connectomics data at a mesoscale level across various species, allowing easy access to relevant literature and databases. * ConnectomeDatabase: a repository to store and disseminate Connectome files.
Proper citation: ConnectomeViewer: Multi-Modal Multi-Level Network Visualization and Analysis (RRID:SCR_008312) Copy
Public data warehouse for searching cell line data extracted from both ATCC and HyperCLDB. The knowledge base uses the Cell Line Ontology, created with the Protege ontology editing tool from the National Center for Biomedical Ontologies (NCBO) and merges concepts from other ontologies, including the Cell Type Ontology. The Cell Line Knowledge Base uses our Cell Line Ontology as the underlying data model. The ontology defines the following cell line attributes: Cell Line ID, Organism, Tissue, Pathology, Growth Mode, MeSH ID. To report errors in the data or to add cell line data to the knowledge base, please email: clbk-data (at) umich.edu
Proper citation: Cell Line Knowledge Base (RRID:SCR_005832) Copy
Astronomical data archive focused on optical, ultraviolet, and near infrared. Used for maximizing scientific accessibility and productivity of astronomical data. MAST hosts data from over dozen missions like Webb, Hubble, TESS, Kepler, and in the future Roman.
Proper citation: Barbara A. Mikulski Archive for Space Telescopes (RRID:SCR_023137) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 1, 2023. Data sharing platform based on the ISA software suite - including an annotation tool and a database - that holds environmental omic data in standards-compliant format. It uses various approaches to provide new discovery, interoperability and integration opportunities for environmental scientists, including the development of tools, databases, standard and ontologies. The main tool for collecting environmental omics data from researchers is the EnvBase data catalogue. The NEBC Toolbox contains a range of tools developed by NEBC to support environmental researchers. The data include next generation sequencing, microarray and ABI sequencing technologies. ISAconfigurator and ISAcreator ensure that the extensive information relating to environmental sampling is consistently collected by the NERC experimentalists, according to the appropriate MIBBI checklist(s), and then reported centrally to NEBC. A local instance of the BII runs as an internal prototype database that will soon provide public and private access to NERC research projects outputs, as appropriate. In accordance with the NERC Data Policy, and when data sets are declared ready for public release, the NEBC team will use the ISAconverter to perform (combined) submissions to the appropriate public repositories (ENA, or SRA, ArrayExpress and PRIDE) to ensure long term stewardship.
Proper citation: NERC Environmental Bioinformatics Centre (RRID:SCR_000526) Copy
A non-governmental, non-profit public database for paleontological data providing researchers and the public with information about the entire fossil record. It has been organized and operated by a multi-disciplinary, multi-institutional, international group of paleobiological researchers. Its purpose is to provide global, collection-based occurrence and taxonomic data for organisms of all geological ages, as well data services to allow easy access to data for independent development of analytical tools, visualization software, and applications of all types. The Database's broader goal is to encourage and enable data-driven collaborative efforts that address large-scale paleobiological questions. Paleontological data files are accepted for upload. However, PaleoBioDB needs some basic data types to be included in order to perform an upload. The Application Programming Interface (API) gives scientists, students, and developers programmatic access to taxonomic, spatial, and temporal data contained within the database.
Proper citation: Paleobiology Database (RRID:SCR_003798) Copy
http://bioinformatics.aecom.yu.edu/index.htm
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. Primary informatics resource for joint research efforts of the Albert Einstein College of Medicine and Montefiore Medical Center to facilitate the study and understanding of biological processes, clinical disorders, pathologic abnormalities, and the relationships among them, using a wide variety of informatics techniques, applications, and user training. Their services include: * Collaboration on research design to enable effective data management throughout all phases of a project * Provision of management capability for large volumes of data generated by microarrays and related technologies * Provision and supports a software toolchest for data capture, retrieval, and analysis * Design and implementation of custom interfaces to incorporate existing or separately designed databases into the central data management architecture * Support for data management for the Biorepository, to enhance specimen storage, identification, and linkage with clinical data * Ensuring conformity of data elements and structures to national standards via participation in standards organizations, facilitating intramural and extramural collaboration * Providing individualized support to end-users with bioinformatics training needs * Serving as a bioinformatics liaison to other research institutes and organizations * Providing data management support for clinical research * Providing a common, secure repository for clinical, experimental, and biosample storage data
Proper citation: Einstein-Montefiore ICTR Research Informatics Core (RRID:SCR_003451) Copy
Database for MHC antigenic peptide of Mycobacterium tuberculosis. It aims to make a comprehensive repository of synthetic antigenic peptides predicted from several MHC predication servers.
Proper citation: PeMtb (RRID:SCR_016278) Copy
Experimental datasets of crystal structures and binding affinities for diverse protein-ligand complexes. Some datasets are generated in house while others are collected from the literature or deposited by academic labs, national centers, and the pharmaceutical industry. For the community to improve their approaches, they need exceptional datasets to train scoring functions and develop new docking algorithms. They aim to provide the highest quality data for a diverse collection of proteins and small molecule ligands. They need input from the community in developing target priorities. Ideal targets will have many high-quality crystal structures (apo and 10-20 bound to diverse ligands) and affinity data for 25 compounds that range in size, scaffold, and logP. It is best if the ligand set has several congeneric series that span a broad range of affinity, with low nanomolar to mid-micromolar being most desirable. They prefer Kd data over Ki data over IC50 data (no % activity data). They will determine solubility, pKa, logP/logD data for the ligands whenever possible. They have augmented some donated IC50 data by determining Kon/Koff and ITC data.
Proper citation: Community Structure-Activity Resource (RRID:SCR_002206) Copy
The primary climate-change data and information analysis center of the U.S. Department of Energy (DOE) and includes the World Data Center for Atmospheric Trace Gases, serving the climate change-related data and information needs of users worldwide. CDIAC''s data holdings include estimates of carbon dioxide emissions from fossil-fuel consumption and land-use changes; records of atmospheric concentrations of carbon dioxide and other radiatively active trace gases; carbon cycle and terrestrial carbon management datasets and analyses; and global/regional climate data and time series. CDIAC provides scientific and data management support for projects sponsored by a number of agencies, including the AmeriFlux Network, continuous observations of ecosystem level exchanges of CO2, water, energy and momentum at different time scales for sites in the Americas; the Ocean CO2 Data Program of CO2 measurements taken aboard ocean research vessels; DOE-supported FACE experiments, which evaluate plant and ecosystem response to elevated CO2 concentrations; and the HIPPO project, which is analyzing the atmospheric carbon cycle and greenhouse gas concentrations from pole to pole over the Pacific Ocean. For those wishing to contribute data to the CDIAC data collection, review the guide and then contact one of the CDIAC staff members to discuss further data submission plans. Data providers may submit data in a variety of ways including via email, direct deposit to a secure CDIAC File Transfer Protocol (FTP) server, on transfer media (e.g. CD-ROM), or by having CDIAC mirror a location at the investigator''s institution.
Proper citation: Carbon Dioxide Information Analysis Center (RRID:SCR_006999) Copy
https://ecl.earthchem.org/view.php?id=329
Database contating hydrothermal spring geochemistry that hosts and serves the full range of compositional data acquired on seafloor hydrothermal vents from all tectonic settings. It can accommodate published historical data as well as legacy and new data that investigators contribute.
Proper citation: VentDB (RRID:SCR_001632) Copy
Web service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. The repository allows you to explore datasets from numerous genotype experiments, supplied by a range of data providers. The EGA''s role is to provide secure access to the data that otherwise could not be distributed to the research community. The EGA contains exclusive data collected from individuals whose consent agreements authorize data release only for specific research use or to bona fide researchers. Strict protocols govern how information is managed, stored and distributed by the EGA project. As an example, only members of the EGA team are allowed to process data in a secure computing facility. Once processed, all data are encrypted for dissemination and the encryption keys are delivered offline. The EGA also supports data access only for the consortium members prior to publication.
Proper citation: European Genome phenome Archive (RRID:SCR_004944) Copy
https://www.genome.wisc.edu/tools/asap.htm
Database and web interface developed to store, update and distribute genome sequence data and gene expression data. ASAP was designed to facilitate ongoing community annotation of genomes and to grow with genome projects as they move from the preliminary data stage through post-sequencing functional analysis. The ASAP database includes multiple genome sequences at various stages of analysis, and gene expression data from preliminary experiments. Use of some of this preliminary data is conditional, and it is the users responsibility to read the data release policy and to verify that any use of specific data obtained through ASAP is consistent with this policy. There are four main routes to viewing the information in ASAP: # a summary page, # a form to query the genome annotations, # a form to query strain collections, and # a form to query the experimental data. Navigational buttons appear on every page allowing users to jump to any of these four points., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: ASAP (RRID:SCR_001849) 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.
