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http://trans.nih.gov/bmap/resources/resources.htm
As part of BMAP gene discovery efforts, mouse brain cDNA libraries and Expressed Sequence Tags (ESTs) have been generated. Through this project a BMAP mouse brain UniGene set consisting of over 24,000 non-redundant members of unique clusters has been developed from EST sequencing of more than 50,000 cDNA clones from 10 regions of adult mouse brain, spinal cord, and retina (http://brainEST.eng.uiowa.edu/). In 2001, NIMH along with NICHD, NIDDK, and NIDA, awarded a contract to the University of Iowa ( M.B. Soares, PI) to isolate full-length cDNA clones corresponding to genes expressed in the developing mouse nervous system and determine their full-coding sequences. The BMAP mouse brain EST sequences can be accessed at NCBI's dbEST database (http://www.ncbi.nlm.nih.gov/dbEST/). Arrayed sets of BMAP mouse brain UniGenes and cDNA libraries, and individual BMAP cDNA clones can be purchased from Open Biosystems, Huntsville, AL (http://www.openbiosystems.com
Proper citation: BMAP cDNA Resources (RRID:SCR_002973) Copy
Database designed for web-based examination of the human erythroid transcriptome. The database is organized to provide a cytogenetic band position, a unique name as well as a concise annotation for each entry. Search queries may be performed by name, keyword or cytogenetic location. Search results are linked to primary sequence data and three major human genome browsers for access to information considered current at the time of each search. Hembase provides interested scientists and clinical hematologists with a genome-based approach toward the study of erythroid biology. Red blood cells in the circulation arise from hematopoietic stem cells that proliferate as erythroid progenitors and differentiate into erythroid precursor cells in response to the hormone erythropoietin. Messenger RNA was isolated from those cells and used to generate gene libraries. Sequencing several thousand expressed sequence tags (EST) from those libraries was then performed. Those EST and sequences encoding several hundred additional genes with known expression in erythroid cells are compiled here as a database of human erythroid gene activity. The database is organized and linked according to the location of these sequences within the human genome., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.
Proper citation: HemBase (RRID:SCR_002880) Copy
Collection of individual databases on members of the steroid and thyroid hormone receptor superfamily. Although the databases are located on different servers and are managed individually, they each form a node of the NRR. The NRR itself integrates the separate databases and allows an interactive forum for the dissemination of information about the superfamily. NRR Components: Androgen receptor, Estrogen receptor, Glucocorticoid receptor, Peroxisome proliferator, Steroid receptor protein, Thyroid receptor, Vitamin D receptor.
Proper citation: Nuclear Receptor Resource (RRID:SCR_003285) Copy
https://hirnetwork.org/consortium/cmai
Consortium that is an independent research initiative of the Human Research Information Network (HIRN). It is developing innovative approaches to model basic aspects of human T1D immunobiology using novel in vivo and in vitro platforms.
Proper citation: HIRN Consortium on Modeling Autoimmune Interactions (RRID:SCR_016200) Copy
https://hirnetwork.org/coordinating_group/hirec
The Bioinformatics Center is located within the Department of Diabetes and Cancer Discovery Science at City of Hope and was established in 2014 to support the Human Islet Research Network (HIRN). The overall objective of the Bioinformatics Center is to advance type 1 diabetes knowledge generated through HIRN by providing the bioinformatics capability and infrastructure needed to support the Network. To achieve this goal, the Bioinformatics Center provides investigators with tools, processes, and methods to facilitate long term sharing, maintenance, and management of HIRN developed resources, including datasets, technologies, documents, and bioreagents. Collaboration and communication are cultivated through consultation and outreach activities. In 2019, HIRN received funding to continue HIRN Coordinating Center (CC) and Bioinformatics Center (BC) as Human Islet Research Enhancement Center (HIREC).
Proper citation: HIRN Bioinformatics Center (RRID:SCR_016203) Copy
Collects and provides data on the human genome and epigenome to facilitate genetic studies of type 2 diabetes and its complications. A component of the AMP T2D consortium, which includes the National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) and an international collaboration of researchers.
Proper citation: Diabetes Epigenome Atlas (RRID:SCR_016441) 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://github.com/hakyimlab/PrediXcan
Software tool to detect known and novel genes associated with disease traits and provide insights into the mechanism of these associations. Used to test the molecular mechanisms through which genetic variation affects phenotype.
Proper citation: PrediXcan (RRID:SCR_016739) Copy
https://www.sciencescott.com/pyminer
Software tool to automate cell type identification, cell type-specific pathway analyses, graph theory-based analysis of gene regulation, and detection of autocrine-paracrine signaling networks. Finds Gene and Autocrine-Paracrine Networks from Human Islet scRNA-Seq.
Proper citation: PyMINEr (RRID:SCR_016990) 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://www.bx.psu.edu/~giardine/vision/
International project to analyze mouse and human hematopoiesis, and provide a tractable system with clear clinical significance and importance to NIDDK. Collection of information from the flood of epigenomic data on hematopoietic cells as catalogs of validated regulatory modules, quantitative models for gene regulation, and a guide for translation of research insights from mouse to human.
Proper citation: ValIdated Systematic IntegratiON of epigenomic data (RRID:SCR_016921) Copy
Ratings or validation data are available for this resource
https://www.zurich.ibm.com/cellcycletracer/
Software tool as supervised machine learning algorithm that classifies and sorts single cell mass cytometry data according to their cell cycle, which allows to correct for cell cycle state and cell volume heterogeneity. Reveals signaling relationships and cell heterogeneity that were otherwise masked. Computational method to quantify cell cycle and cell volume variability.
Proper citation: CellCycleTRACER (RRID:SCR_017128) Copy
https://repository.niddk.nih.gov/network/284
Group of collaborating investigators who conduct long-term studies and clinical trials of the most commonly used surgical, pharmacological, and behavioral approaches for management of urinary incontinence in women diagnosed with stress and mixed incontinence.
Proper citation: Urinary Incontinence Treatment Network (RRID:SCR_001543) Copy
https://www.searchfordiabetes.org/
National multi-center study aimed at understanding more about diabetes among children and young adults in the United States less than 20 years of age in six geographically dispersed populations that encompass the ethnic diversity of the United States. SEARCH has been helping to find answers about the types of diabetes, its complications, and how having diabetes affects the lives of children and young adults. There are more than 20,000 study participants representing all different racial and ethnic backgrounds who have helped SEARCH determine the extent of diabetes in the community and its impact on different populations. The SEARCH Study invites Investigators interested in childhood Diabetes Research to collaborate on matters of interest to the field of childhood Diabetes.
Proper citation: SEARCH for Diabetes in Youth (RRID:SCR_001540) Copy
Consortium comprised of six clinical centers and a data coordinating center to facilitate coordinated clinical, epidemiological, and behavioral research in the field of bariatric surgery, through the cooperative development of common clinical protocols and a bariatric surgery database that will collect information from participating clinical centers. LABS will help pool the necessary clinical expertise and administrative resources to facilitate the conduct of multiple clinical studies in a timely, efficient manner. Also, the use of standardized definitions, clinical protocols, and data-collection instruments will enhance the investigator's ability to provide meaningful evidence-based recommendations for patient evaluation, selection, and follow-up care. The consortium was funded in September 2003. The investigators have collaboratively developed a core database and clinical protocols, and subject enrollment began in early 2005. A repository of data and biological specimens for future research also will be collected by the centers participating in LABS. These will provide valuable resources for future study of obesity and its complications.
Proper citation: Longitudinal Assessment of Bariatric Surgery (RRID:SCR_001536) Copy
Web based integrative platform for transcriptional regulation studies.
Proper citation: Cistrome (RRID:SCR_000242) Copy
http://archives.niddk.nih.gov/patient/mpsa/mpsa.aspx
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Cross-disciplinary, multi-institutional network with wide range of experts to analyze serum and tissue samples collected in the Medical Therapy of Prostatic Symptoms (MTOPS) trial. Consortium aims to discover and validate biomarkers for the detection, risk assessment, and disease progression assessment of benign prostatic hyperplasia (BPH).
Proper citation: MTOPS Prostate Samples Analysis Consortium (RRID:SCR_000041) Copy
Publications from a multi-center, longitudinal, observational study examining the risk factors associated with the long-term complications of type 1 diabetes. The study began in 1994 and follows the 1441 participants previously enrolled in the Diabetes Control and Complications Trial (DCCT), http://diabetes.niddk.nih.gov/dm/pubs/control/index.aspx. The primary aim of EDIC is to examine the long-term effects of conventional vs. intensive diabetes treatment received during the DCCT on the subsequent development and progression of microvascular, neuropathic and cardiovascular complications. This involves studying the influence of genetic factors and other factors such as HbA1c, blood pressure, lipid levels, and treatment modalities on the development and progression of these complications. Annual or biennial measurements (using DCCT methods, standardized protocols and central laboratories) of vascular events, albumin excretion, GFR, ECG, ankle-brachial BP index, serum lipids and HbA1c allows the following analyses: 1) continuation of intention-to-treat analyses to determine long-term effects of prior separation of glycemic levels; 2) risk factors for macrovascular outcomes; 3) correlation of progression of micro- and macrovascular outcomes. The current updated version of the EDIC Protocol is available for download. EDIC is made up of 28 clinical centers, one data coordinating center and one clinical coordinating center.
Proper citation: Epidemiology of Diabetes Interventions and Complications (RRID:SCR_001468) Copy
The NIDDK Information Network (dkNET) is a community-based network to serve needs of basic and clinical investigators that includes large pools of data and research resources relevant to mission of National Institute of Diabetes and Digestive and Kidney Disease.
Proper citation: NIDDK Information Network (dkNET) (RRID:SCR_001606) Copy
https://clinicaltrials.gov/study/NCT01619475
Study consisting of nine liver transplant centers with expertise in adult living-donor liver transplantation (LDLT) and a central data coordinating center to provide valuable information on the outcomes of adult to adult living donor liver transplantation (AALDLT) to aid decisions made by physicians, patients, and potential donors. The study will establish and maintain the infrastructure required to accrue and follow sufficient numbers of patients being considered for and undergoing AALDLT to provide generalizable data from adequately powered studies. The major aims of A2ALL are as follows: * Quantify the impact of choosing LDLT on the candidate for transplantation * Characterize the difference between LDLT and deceased donor liver transplant (DDLT) in terms of post-transplant outcomes, including patient and graft survival, surgical morbidity, and resource utilization on the recipient of a transplant * Determine the short- and long-term health and quality of life (QOL) impact of donation, including (a) morbidity after liver donation and (b) long-term health-related QOL of donors. * Standardize and assess the role of informed consent in affecting the decision to donate and satisfaction after living liver donation * Other aims include comparison of the severity of recurrence of hepatocellular carcinoma for DDLT versus LDLT, the systematic characterization of liver regeneration and function in donors and recipients, the evaluation of the differences in the immune response to LDLT versus DDLT, and the establishment of a robust data and sample repository on liver transplantation that may be used to study clinical and biological questions as new technologies and resources become available. Patients enrolled in the study will be followed and managed in a standardized fashion.
Proper citation: Adult to Adult Living Donor Liver Transplantation Cohort Study (RRID:SCR_001494) Copy
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