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http://www.niaid.nih.gov/topics/transplant/research/Pages/fundedBasics.aspx#NHPTCSP
Cooperative program for research on nonhuman primate models of kidney, islet, heart, and lung transplantation evaluating the safety and efficacy of existing and new treatment regimens that promote the immune system''''s acceptance of a transplant and to understand why the immune system either rejects or does not reject a transplant. This program bridges the critical gap between small-animal research and human clinical trials. The program supports research into the immunological mechanisms of tolerance induction and development of surrogate markers for the induction, maintenance, and loss of tolerance.
Proper citation: Nonhuman Primate Transplantation Tolerance Cooperative Study Group (RRID:SCR_006847) Copy
http://diabetes.niddk.nih.gov/dm/pubs/america/
A compilation and assessment of epidemiologic, public health, and clinical data on diabetes and its complications in the United States. Published by the National Diabetes Data Group of the National Institute of Diabetes and Digestive and Kidney Diseases, the book contains 36 chapters organized in five areas: * the descriptive epidemiology of diabetes in the United States based on national surveys and community-based studies, including prevalence, incidence, sociodemographic and metabolic characteristics, risk factors for developing diabetes, and mortality * the myriad complications that affect patients with diabetes * characteristics of therapy and medical care for diabetes * economic aspects, including health insurance and health care costs * diabetes in special populations, including African Americans, Hispanics, Asian and Pacific Islanders, Native Americans, and pregnant women. Diabetes in America, 2nd Edition, has been designed to serve as a reliable scientific resource for assessing the scope and impact of diabetes and its complications, determining health policy and priorities in diabetes, and identifying areas of need in research. The intended audience includes health policy makers at the local and Federal levels who need a sound quantitative base of knowledge to use in decision making; clinicians who need to know the probability that their patients will develop diabetes and the prognosis of the disease for complications and premature mortality; persons with diabetes and their families who need sound information on which to make decisions about their life with diabetes; and the research community which needs to identify areas where important scientific knowledge is lacking.
Proper citation: Diabetes in America (RRID:SCR_006754) Copy
Online community for industry news and careers for life science professionals.
Proper citation: BioSpace (RRID:SCR_012010) Copy
Consortium that aims to improve the efficiency of the medicine development process by better incorporating estimates of relative effectiveness into drug development and to enrich decision-making by regulatory authorities and health technology assessment (HTA) bodies through: * Bringing together regulators, HTA bodies, academics, companies, patients and other societal stakeholders; * Assessing existing processes, methodologies, and key research issues; * Proposing innovative (and more pragmatic) trial designs and assessing the value of information; * Proposing and testing innovative analytical and predictive modelling approaches; * Assessing operational, ethical, regulatory issues and proposing and testing solutions; * Creating new decision making frameworks, and building open tools to allow for the evaluation of development programs and use in the assessment of the value of new medicines; * Sharing and discussing deliverables with, among others, Pharmaceutical companies, regulatory authorities, HTA / reimbursement agencies, clinicians and patient organizations; * Developing training activities for researchers, decision makers and societal stakeholders in the public and private sector in order to increase knowledge about various aspects of relative effectiveness. The expected impact is that it will contribute to the knowledge base, particularly to inform clinical decision making and improve the efficiency of the R&D process. GETREAL will help to generate a consensus on best practice in the timing, performance and use of real life clinical studies in regulatory and reimbursement decision-making. It will also help to create a strong platform for the communication of results and for future discussions in this important area.
Proper citation: GetReal (RRID:SCR_003862) Copy
http://www.asiancancerresearchgroup.org/
An independent, not-for-profit consortium to accelerate research, and improve treatment for patients affected with the most commonly-diagnosed cancers in Asia by generating a genomic data resource for the most prevalent cancers in Asia. ACRG is focusing its initial efforts on Asian liver, gastric and lung cancers. Goals * Generate comprehensive genomics data sets for Asia-prevalent cancers * Conduct all research under good clinical practices and in accordance with local laws * Uncover key mutations and pathways for developing targeted therapies * Discover molecular tumor classifiers for patient stratification * Discover prognostic markers to identify high-risk patients * Freely share resulting raw data with scientific community to empower researchers globally and enable development of new diagnostics and medicines * Publish data analysis results jointly in prominent scientific journals Over the next two years, Lilly, Merck and Pfizer have committed to create an extensive pharmacogenomic cancer database that will be composed of data from approximately 2,000 tissue samples from patients with lung and gastric cancer that will be made publicly available to researchers and, over time, further populated with clinical data from a longitudinal analysis of patients. Comparison of the contrasting genomic signatures of these cancers could inform new approaches to treatment. Lilly has assumed responsibility for ultimately providing the data to the research public through an open-source concept managed by Lilly''''s Singapore research site. Moreover, Lilly, Merck and Pfizer will each provide technical and intellectual expertise. One dataset can be found at http://gigadb.org/dataset/100034
Proper citation: Asian Cancer Research Group (RRID:SCR_004001) Copy
http://humanconnectome.org/connectome/connectomeDB.html
Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.
Proper citation: ConnectomeDB (RRID:SCR_004830) Copy
http://alzheimers.med.umich.edu/
An Alzheimer's disease center which aims to conduct and promote research on Alzheimer's disease and enhance public and professional understanding of dementia through education and outreach efforts. The MADC promotes clinical research on memory and aging which involves the direct use of research volunteers, biomarkers, and other clinical data collected through the University of Michigan Memory and Aging Project.
Proper citation: Michigan Alzheimer's Disease Center (RRID:SCR_008773) Copy
Site for collection and distribution of clinical data related to genetic analysis of drug abuse phenotypes. Anonymous data on family structure, age, sex, clinical status, and diagnosis, DNA samples and cell line cultures, and data derived from genotyping and other genetic analyses of these clinical data and biomaterials, are distributed to qualified researchers studying genetics of mental disorders and other complex diseases at recognized biomedical research facilities. Phenotypic and Genetic data will be made available to general public on release dates through distribution mechanisms specified on website.
Proper citation: National Institute on Drug Abuse Center for Genetic Studies (RRID:SCR_013061) Copy
Provides Prism softwares and services that integrate advanced imaging into the clinical workflow for brain mapping from acquisition through processing, visualization, and export to PACS. Prism integrates functional MRI, diffusion MRI, perfusion, MR spectroscopy, and PET/CT into a unified workflow for diagnosis and treatment planning in brain disorders. Processing is also available as a cloud deployed service, Prism Serve. Research support includes import/export for imaging and derived quantitative data in both DICOM and research formats such as AFNI and Trackviz.
Proper citation: Prism Clinical Imaging (RRID:SCR_016977) Copy
https://t1dexchange.org/research/biobank/
Collection of biological samples linked to participant medical data from individuals living with type 1 diabetes. Unifies samples and data from eight different clinical studies related to type 1 diabetes.
Proper citation: T1D Exchange Biobank (RRID:SCR_017195) Copy
Consortium to bring together clinicians, pathologists, researchers, and biotech innovators to create scalable network of stakeholders interested in helping patients with glomerular kidney disease. Makes collective expertise of its members available for discussion of individual cases, provides infrastructure for biomarker studies, enables genomic research, and facilitates clinical trials.
Proper citation: Glomerular Disease Study & Trial Consortium (RRID:SCR_017264) Copy
Software tool for practical self assessment and reporting method for clinical research studies, to capture key information about data acquisition and quality control measures. Linked to dataset so that potential research collaborators can determine if data meets their needs and expectations.
Proper citation: DAQCORD (RRID:SCR_017395) Copy
https://bioconductor.org/packages/TCGAbiolinks/
Software R Bioconductor package for integrative analysis with TCGA data.TCGAbiolinks is able to access National Cancer Institute Genomic Data Commons thorough its GDC Application Programming Interface to search, download and prepare relevant data for analysis in R.
Proper citation: TCGAbiolinks (RRID:SCR_017683) Copy
A web-based neuroimaging and neuropsychology software suite that offers versatile, automatable data upload/import/entry options, rapid and secure sharing of data among PIs, querying and export all data, real-time reporting, and HIPAA and IRB compliant study-management tools suitable to large institutions as well as smaller scale neuroscience and neuropsychology researchers. COINS manages over over 400 studies, more than 265,000 clinical neuropsychological assessments, and 26,000 MRI, EEG, and MEG scan sessions collected from 18,000 participants at over ten institutions on topics related to the brain and behavior. As neuroimaging research continues to grow, dynamic neuroinformatics systems are necessary to store, retrieve, mine and share the massive amounts of data. The Collaborative Informatics and Neuroimaging Suite (COINS) has been created to facilitate communication and cultivate a data community. This tool suite offers versatile data upload/import/entry options, rapid and secure sharing of data among PIs, querying of data types and assessments, real-time reporting, and study-management tools suitable to large institutions as well as smaller scale researchers. It manages studies and their data at the Mind Research Network, the Nathan Kline Institute, University of Colorado Boulder, the Olin Neuropsychiatry Research Center (at) Hartford Hospital, and others. COINS is dynamic and evolves as the neuroimaging field grows. COINS consists of the following collaboration-centric tools: * Subject and Study Management: MICIS (Medical Imaging Computer Information System) is a centralized PostgreSQL-based web application that implements best practices for participant enrollment and management. Research site administrators can easily create and manage studies, as well as generate reports useful for reporting to funding agencies. * Scan Data Collection: An automated DICOM receiver collects, archives, and imports imaging data into the file system and COINS, requiring no user intervention. The database also offers scan annotation and behavioral data management, radiology review event reports, and scan time billing. * Assessment Data Collection: Clinical data gathered from interviews, questionnaires, and neuropsychological tests are entered into COINS through the web application called Assessment Manager (ASMT). ASMT's intuitive design allows users to start data collection with little or no training. ASMT offers several options for data collection/entry: dual data entry, for paper assessments, the Participant Portal, an online tool that allows subjects to fill out questionnaires, and Tablet entry, an offline data entry tool. * Data Sharing: De-identified neuroimaging datasets with associated clinical-data, cognitive-data, and associated meta-data are available through the COINS Data Exchange tool. The Data Exchange is an interface that allows investigators to request and share data. It also tracks data requests and keeps an inventory of data that has already been shared between users. Once requests for data have been approved, investigators can download the data directly from COINS.
Proper citation: Mind Research Network - COINS (RRID:SCR_000805) Copy
https://kidsfirstdrc.org/portal/portal-features/
Portal for analysis and interpretation of pediatric genomic and clinical data to advance personalized medicine for detection, therapy, and management of childhood cancer and structural birth defects. For patients, researchers, and clinicians to create centralized database of well curated clinical and genetic sequence data from patients with childhood cancer or structural birth defects.
Proper citation: Kids First Data Resource Portal (RRID:SCR_016493) Copy
Web interface that facilitates open science for neuroscience community by simplifying global access to and sharing of datasets and tools. Portal internalizes typical data cycle of research project, beginning with data acquisition, followed by data processing with published tools, and ultimately publication of results with link to original dataset. Platform to form interactive network of collaborations in brain research, interdisciplinary student training, international partnerships, clinical translation and open publishing. Provides unified interface to Canadian neuroscience research community. Open neuroscience research with sharing of both data and methods, to create large-scale databases, development of standards for sharing, facilitation of advanced analytic strategies, open dissemination to global community of neuroscience data and methods, and establishment of training programs for next generation of computational neuroscience researchers.
Proper citation: Canadian Open Neuroscience Platform (RRID:SCR_016433) Copy
https://www.denovosoftware.com/?gclid=EAIaIQobChMI36rn3-Dd3AIV2ud3Ch27lw2oEAAYASAAEgLbRvD_BwE
Software tool for flow and image cytometry data analysis by De Novo Software company.
Proper citation: FCS Express (RRID:SCR_016431) Copy
Software tool for data management in clinical studies to improve care for patients with Traumatic Brain Injury (TBI). Used to search and find study variables with the associated information and export study data for further analysis.
Proper citation: INCF-Neurobot (RRID:SCR_017004) Copy
Nonprofit academic medical center focused on integrated clinical practice, education, and research with three major campuses: Rochester, Minnesota; Jacksonville, Florida; and Phoenix/Scottsdale, Arizona. Practice specializes in treating difficult cases through tertiary care and destination medicine.
Proper citation: Mayo Clinic (RRID:SCR_011383) Copy
http://research.nhgri.nih.gov/CGD/
Manually curated database of all conditions with known genetic causes, focusing on medically significant genetic data with available interventions. Includes gene symbol, conditions, allelic conditions, inheritance, age in which interventions are indicated, clinical categorization, and general description of interventions/rationale. Contents are intended to describe types of interventions that might be considered. Includes only single gene alterations and does not include genetic associations or susceptibility factors related to more complex diseases.
Proper citation: Clinical Genomic Database (RRID:SCR_006427) Copy
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