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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
Freely available tool for Gene-centered collection and display of DNA variations. It also provides patient-centered data storage and storage of Next Generation Sequencing (NGS) data, even of variants outside of genes. Please note that LOVD provides a system for storage of information on genes and allelic variants. To obtain information about any genes or variants, do not download the LOVD package. This information should be obtained from the respective databases, http://www.lovd.nl/2.0/index_list.php In total: 2,507,027 variants (2,208,937 unique) in 170,935 individuals in 62619 genes in 88 LOVD installations. (Aug. 2013) LOVD 3.0 shared installation, http://databases.lovd.nl/shared/genes To maintain a high quality of the data stored, LOVD connects with various resources, like HGNC, NCBI, EBI and Mutalyzer. You can download LOVD in ZIP and GZIPped TARball formats.
Proper citation: Leiden Open Variation Database (RRID:SCR_006566) Copy
Data archive of more than 500,000 files of research in the social sciences, hosting 16 specialized collections of data in education, aging, criminal justice, substance abuse, terrorism, and other fields. ICPSR comprises a consortium of about 700 academic institutions and research organizations providing training in data access, curation, and methods of analysis for the social science research community. ICPSR welcomes and encourages deposits of digital data. ICPSR's educational activities include the Summer Program in Quantitative Methods of Social Research external link, a comprehensive curriculum of intensive courses in research design, statistics, data analysis, and social methodology. ICPSR also leads several initiatives that encourage use of data in teaching, particularly for undergraduate instruction. ICPSR-sponsored research focuses on the emerging challenges of digital curation and data science. ICPSR researchers also examine substantive issues related to our collections, with an emphasis on historical demography and the environment.
Proper citation: Inter-university Consortium for Political and Social Research (ICPSR) (RRID:SCR_003194) Copy
Platform to support research and enable collaboration. Used to discover projects, data, materials, and collaborators helpful to your own research.
Proper citation: Open Science Framework (RRID:SCR_003238) Copy
Computing resources structural biologists need to discover the shapes of the molecules of life, it provides access to web-enabled structural biology applications, data sharing facilities, biological data sets, and other resources valuable to the computational structural biology community. Consortium includes X-ray crystallography, NMR and electron microscopy laboratories worldwide.SBGrid Service Center is located at Harvard Medical School.SBGrid's NIH-compliant Service Center supports SBGrid operations and provides members with access to Software Maintenance, Computing Access, and Training. Consortium benefits include: * remote management of your customized collection of structural biology applications on Linux and Mac workstations; * access to commercial applications exclusively licensed to members of the Consortium, such as NMRPipe, Schrodinger Suite (limited tokens) and the Incentive version of Pymol; remote management of supporting scientific applications (e.g., bioinformatics, computational chemistry and utilities); * access to SBGrid seminars and events; and * advice about hardware configurations, operating system installations and high performance computing. Membership is restricted to academic/non-profit research laboratories that use X-ray crystallography, 2D crystallography, NMR, EM, tomography and other experimental structural biology technologies in their research. Most new members are fully integrated with SBGrid within 2 weeks of the initial application.
Proper citation: Structural Biology Grid (RRID:SCR_003511) Copy
The Cancer Text Information Extraction System (caTIES) provides tools for de-identification and automated coding of free-text structured pathology reports. It also has a client that can be used to search these coded reports. The client also supports Tissue Banking and Honest Broker operations. caTIES focuses on two important challenges of bioinformatics * Information extraction (IE) from free text * Access to tissue. Regarding the first challenge, information from free-text pathology documents represents a vital and often underutilized source of data for cancer researchers. Typically, extracting useful data from these documents is a slow and laborious manual process requiring significant domain expertise. Application of automated methods for IE provides a method for radically increasing the speed and scope with which this data can be accessed. Regarding the second challenge, there is a pressing need in the cancer research community to gain access to tissue specific to certain experimental criteria. Presently, there are vast quantities of frozen tissue and paraffin embedded tissue throughout the country, due to lack of annotation or lack of access to annotation these tissues are often unavailable to individual researchers. caTIES has three goals designed to solve these problems: * Extract coded information from free text Surgical Pathology Reports (SPRs), using controlled terminologies to populate caBIG-compliant data structures. * Provide researchers with the ability to query, browse and create orders for annotated tissue data and physical material across a network of federated sources. With caTIES the SPR acts as a locator to tissue resources. * Pioneer research for distributed text information extraction within the context of caBIG. caTIES focuses on IE from SPRs because they represent a high-dividend target for automated analysis. There are millions of SPRs in each major hospital system, and SPRs contain important information for researchers. SPRs act as tissue locators by indicating the presence of tissue blocks, frozen tissue and other resources, and by identifying the relationship of the tissue block to significant landmarks such as tumor margins. At present, nearly all important data within SPRs are embedded within loosely-structured free-text. For these reasons, SPRs were chosen to be coded through caTIES because facilitating access to information contained in SPRs will have a powerful impact on cancer research. Once SPR information has been run through the caTIES Pipeline, the data may be queried and inspected by the researcher. The goal of this search may be to extract and analyze data or to acquire slides of tissue for further study. caTIES provides two query interfaces, a simple query dashboard and an advanced diagram query builder. Both of these interfaces are capable of NCI Metathesaurus, concept-based searching as well as string searching. Additionally, the diagram interface is capable of advanced searching functionalities. An important aspect of the interface is the ability to manage queries and case sets. Users are able to vet query results and save them to case sets which can then be edited at a later time. These can be submitted as tissue orders or used to derive data extracts. Queries can also be saved, and modified at a later time. caTIES provides the following web services by default: MMTx Service, TIES Coder Service
Proper citation: caTIES - Cancer Text Information Extraction System (RRID:SCR_003444) Copy
A three-year consortium that brings together insurers and health care providers to share information from approximately 9 million patients, with a goal that insights from the data will bring down healthcare costs and improve outcomes. It aims to be one of the largest health information exchanges in the country, with the goal of better connecting the vast, often disparate healthcare landscape across California. The database that will house patient data will be overseen by Orion Health, an independent eHealth software company. The information will only be used for clinical purposes. Academic research institutions can apply to use the Cal INDEX de-identified data for research to benefit the public good, such as population health initiatives. Cal INDEX has five main goals: * Improve the quality of care by providing clinicians with a unified statewide source of integrated patient information * Provide patients with a seamless transition between health plans or across various healthcare professionals and hospitals * Improve efficiency and reduce the cost of healthcare * Encourage healthcare technology innovation * Improve public health by providing de-identified data for medical research. Cal INDEX plans to launch at the end of 2014 with approximately 9 million health information records from combined members of Dignity Health and Blue Shield of California and Anthem Blue Cross. Cal INDEX is open to any health data contributor. Cal INDEX will establish a bi-directional data interface with providers to exchange data with EMRs and other hospital and office-based systems.
Proper citation: California Integrated Data Exchange (RRID:SCR_003747) Copy
A consortium that seeks to provide an integrated approach to anti-drug immunization by evaluating immunogenicity in hemophilia A, multiple sclerosis, and inflammatory diseases, and exploring new tools for protein drug immunogenicity. The data collected will be pooled in a single immunogenicity databank and will be standardized and used to develop models of anti-drug antibodies. By examining the correlation between patient and clinical factors and the incidence of immunogenicity, it hopes to reduce the regulatory and resource burdens of immunogenicity testing. The objectives of the consortium are: # Access to large cohorts of patients treated with marketed biopharmaceutical products # Complementary expertise for anti-drug antibodies (ADA) assays; standardization and characterization of ADA # Novel integrated approaches to characterize anti-drug lymphocyte responses # Development and validation of innovative prediction tools # Collection and integration of immunogenicity-related data and clinical relevance of ADA ABIRISK is grouped into five working projects, which communicate with one another and provide each other with results and data for analysis. The five working projects are: ADA assay development and validation and cohort management; cellular characterization and mechanisms of the AD immune response; evaluation and development of technologies for predicting immunogenicity; establishment of database, data analyses and integration; and project management and communication.
Proper citation: ABIRISK (RRID:SCR_003740) Copy
A not-for-profit membership organization and educational charity that facilitates collaborative data sharing projects in the pharmaceutical, cosmetics and chemistry-related industries specializing in the development of expert computer systems for toxicity and metabolism prediction. They provide a number of extensive and continually updated knowledge bases and the software needed to interrogate them. Its charitable aims include the sponsorship of activities that advance scientific knowledge and understanding and they regularly support computational chemistry events and initiatives that are of interest to Lhasa Limited members and the wider scientific community. All applications for sponsorship will be considered on their individual merits.
Proper citation: Lhasa Limited (RRID:SCR_003775) Copy
Research informatics and analytics platform for the IMI OncoTrack consortium.
Proper citation: eTRIKS (RRID:SCR_003765) Copy
http://www.antilope-project.eu/
Consortium focused on making electronic health data more interoperable, both within and outside of Europe, with the intention to create, validate, and disseminate standard methods to test and certify electronic health solutions and services. In particular it will: Drive the adoption of recognized sets of profiles and underlying standards for eHealth interoperability, and improve the impact of the EU and International eHealth standards development process; Define and validate testing guidelines and common approaches on Interoperability Labelling and Certification processes at European and at National / Regional level. Four work packages were created to provide guidelines, recommendations and frameworks based on a set of use cases, related profiles and standards, Interoperability Quality Management System, testing guidelines and Certification process. All the deliverables will be presented for validation and promotion by organizing workshops across Europe.
Proper citation: Antilope Project (RRID:SCR_003829) Copy
A consortium of leading biobanks and international researchers from all domains of biobanking science to ensure the development of harmonized measures and standardized computing infrastructures enabling the effective pooling of data and key measures of life-style, social circumstances and environment, as well as critical sub-components of the phenotypes associated with common complex diseases. The overall aim is to build upon tools and methods available to achieve solutions for researchers to use pooled data from different cohort and biobank studies. This, in order to obtain the very large sample sizes needed to investigate current questions in multifactorial diseases, notably on gene-environment interactions. This aim will be achieved through the development of harmonization and standardization tools, implementation of these tools and demonstration of their applicability. BioSHaRE researchers are collaborating with P3G, the Global Alliance for Genomics and Health, IRDiRC (International Rare Diseases Research Consortium), H3Africa and other organizations on the development of an International Code of Conduct for Genomic and Health-Related Data Sharing. A draft version is available for external review. Generic documents have been prepared covering areas of biobanking that are of major importance. SOPs have been finalized for blood withdrawal (SOPWP5001blood withdrawal), manual blood processing (SOPWP5002blood processing), shipping of biosamples (SOPWP5003shipping) and withdrawal, processing and storage of urine samples (SOPWP5004urine).
Proper citation: BioSHaRE (RRID:SCR_003811) Copy
http://www.transceleratebiopharmainc.com/
A non-profit research organization aiming to accelerate drug development by increasing the quality and efficiency of clinical studies through the development of shared tools, methods, and platforms. Consortium partnerships are limited to pharmaceutical and biotechnology companies with research & development operations, although there are collaborations with external organizations such the Clinical Data Interchange Standards Consortium (CDISC). Its current focus is to collaborate on: * Standardizing risk-based monitoring * Development of methods to qualify and train clinical trial sites * Development of a common investigator web portal * Development of clinical data standards on efficacy, and methods for comparator drug trials It currently has 5 projects: # Standardized Approach for High-Quality, Risk-Based Monitoring program aims to develop an industry-wide standard and approach for risk-based monitoring of clinical trials in order to enhance patient safety and ensure the quality of clinical trial data. # Shared Site Qualification and Training program aims to standardize GCP training and site qualification credentials in order to realize efficiencies and accelerate study start-up timelines. # Common Investigator Site Portal is a platform designed to streamline investigator and site access through harmonized delivery of content and services. # Data Standards project is a partnership with CDISC to develop industry-wide data standards in priority therapeutic areas to support the exchange and submission of clinical research and meta-data, improving patient safety and outcomes. # Comparator Drugs project aims to establish reliable, rapid sourcing of quality products for use in clinical trials through a comparator supply model enabling accelerated trial timelines and enhanced patient safety.
Proper citation: TransCelerate BioPharma (RRID:SCR_003728) Copy
https://www.projectdatasphere.org/
Initiative to advance oncology research by enabling collaborative sharing of historical oncology clinical trial data through a universal platform (database). The initiative aims to network all stakeholders in the cancer community researchers, industry, academia, advocacy, and other organizations to share insights and collaborate on issues that could not be solved individually. To do this, they have made efforts to address issues of data privacy, security, intellectual property, resources, and incentives as part of its effort to maximize participation. Data contributions include control arms of clinical trials, and the platform uses data-security precautions and analytics to pool multiple studies associated with the same diagnosis in a manner that seeks to protect the privacy of patients and the security of the data contributed.
Proper citation: Project Data Sphere (RRID:SCR_003726) Copy
http://www.themmrf.org/research-programs/commpass-study/
A personalized medicine initiative to discover biomarkers that can better define the biological basis of multiple myeloma to help stratify patients. This effort hopes to obtain samples from approximately 1,000 multiple myeloma patients and follow them over time to identify how a patient's genetic profile is related to clinical progression and treatment response. As a partnership between 17 academic centers, 5 pharmaceuticals and the Department of Veterans Affairs, the goal of this eight year study is to create a database that can accelerate future clinical trials and personalized treatment strategies. MMRF's CoMMpass Study has the following goals: * Create a guide to which treatments work best for specific patient subgroups. * Share data with researchers to accelerate drug development for specific subtypes of multiple myeloma patients. In order to facilitate discoveries and development related to targeted therapies, the comprehensive data from CoMMpass is placed in an open-access research portal. The data will be part of the Multiple Myeloma Research Foundation's (MMRF) Personalized Medicine Platform combines CoMMpass data with those collected from MMRF's Genomics Initiative. It is hoped that the longitudinal data, combined with the annotated bio-specimens will help provide insights that can accelerate personalized therapies.
Proper citation: MMRF CoMMpass Study (RRID:SCR_003721) Copy
Standard specification for organizing and describing outputs of neuroimaging experiments. Used to organize and describe neuroimaging and behavioral data by neuroscientific community as standard to organize and share data. BIDS prescribes file naming conventions and folder structure to store data in set of already existing file formats. Provides standardized templates to store associated metadata in form of Javascript Object Notation (JSON) and tab-separated value (TSV) files. Facilitates data sharing, metadata querying, and enables automatic data analysis pipelines. System to curate, aggregate, and annotate neuroimaging databases. Intended for magnetic resonance imaging data, magnetoencephalography data, electroencephalography data, and intracranial encephalography data.
Proper citation: Brain Imaging Data Structure (BIDs) (RRID:SCR_016124) Copy
A forum for preclinical data sharing and interpretation to enhance its utility for clinical research and development. The forum allows researchers to communicate and collaborate on modern preclinical issues and data sharing.
Proper citation: Preclinical Data Forum Network (RRID:SCR_014545) Copy
Data management platform and data repository based on the CKAN tool for managing and publishing collections of data. It enables the user to search for data, register published datasets, create and manage groups of datasets, and get updates from datasets and groups of interest.
Proper citation: Datahub (RRID:SCR_003996) Copy
http://www.investigatordatabank.org/
Consortium between several pharmaceutical companies to develop a database that shares clinical trial investigator information that each company has on file to reduce administrative burden for investigators and to increase visibility of qualified investigators to research sponsors. Hosted by a 3rd party, DrugDev, it is the one place where pharmaceutical companies can share investigator and site information and investigators can view, edit, and comment on their own information. Industry members will be able share information from their clinical trial management systems including investigator / site contact details, GCP training records, past trial participation, and recruitment history. Upon investigator opt-in, this information is used by each participating company to identify sites for upcoming studies; to help set recruitment targets and timelines; and to share start-up documents such as CV, GCP, and site profile forms. The Databank has grown to include nearly 180,000 investigators (May 2014) and is already bringing benefits to its member companies in identifying qualified investigators for their studies. It also reported the inclusion of 7,335 protocols and 50K sites, representing a patient population around 1.9M.
Proper citation: Investigator Databank (RRID:SCR_003866) Copy
An experimental course and blog offered by the Harvard-Smithsonian Center for Astrophysics John G. Wolbach Library and the Harvard Library to train librarians to respond to the growing data needs of their communities. Data science techniques are becoming increasingly important to all fields of scholarship. In the hands-on course, librarians learn the latest tools for extracting, wrangling, storing, analyzing, and visualizing data. By experiencing the research data lifecycle themselves, librarians develop the data savvy skills that can help transform the services they offer. Material will be made available via the DST4L website as it progresses.
Proper citation: Data Scientist Training for Librarians (RRID:SCR_004124) Copy
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