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.
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://github.com/epistasislab/hibachi
Software tool that creates data sets with particular characteristics. Method and open source software for simulating complex biological and biomedical data to aid in comparing and evaluating machine learning methods.
Proper citation: Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (RRID:SCR_017140) Copy
Diabetes research center which provides patient care and performs diabetes research. Its primary aim is to provide a facilitating framework for conducting multi-disciplinary basic and clinical research and to encourage the scientific development of young investigators.
Proper citation: Joslin Diabetes Center (RRID:SCR_009019) Copy
http://oligogenome.stanford.edu/
The Stanford Human OligoGenome Project hosts a database of capture oligonucleotides for conducting high-throughput targeted resequencing of the human genome. This set of capture oligonucleotides covers over 92% of the human genome for build 37 / hg19 and over 99% of the coding regions defined by the Consensus Coding Sequence (CCDS). The capture reaction uses a highly multiplexed approach for selectively circularizing and capturing multiple genomic regions using the in-solution method developed in Natsoulis et al, PLoS One 2011. Combined pools of capture oligonucleotides selectively circularize the genomic DNA target, followed by specific PCR amplification of regions of interest using a universal primer pair common to all of the capture oligonucleotides. Unlike multiplexed PCR methods, selective genomic circularization is capable of efficiently amplifying hundreds of genomic regions simultaneously in multiplex without requiring extensive PCR optimization or producing unwanted side reaction products. Benefits of the selective genomic circularization method are the relative robustness of the technique and low costs of synthesizing standard capture oligonucleotide for selecting genomic targets.
Proper citation: OligoGenome (RRID:SCR_006025) Copy
Communication network of current and potential biomedical research investigators and technical personnel from traditionally under-served communities: African American, Hispanic American, American Indian, Alaskan Native, Native Hawaiian, and other Pacific Islanders. The major objective of the network is to encourage and facilitate participation of members of underrepresented racial and ethnic minority groups in the conduct of biomedical research in the fields of diabetes, endocrinology, metabolism, digestive diseases, nutrition, kidney, urologic and hematologic diseases. A second objective is to encourage and enhance the potential of the underrepresented minority investigators in choosing a biomedical research career in these fields. An important component of this network is promotion of two-way communications between network members and the NIDDK.
Proper citation: Network of Minority Health Research Investigators (RRID:SCR_006589) Copy
Educational resource to increase awareness of kidney disease and its risk factors, improve early detection of chronic kidney disease (CKD), reduce the burden of CKD, facilitate identification of patients at greatest risk for progression to kidney failure, stress the importance of testing those at risk, promote evidence-based interventions to slow progression of CKD, and support the coordination of Federal responses to CKD. Target audiences include individuals at risk, particularly those with diabetes, high blood pressure, and a family history of kidney disease, and primary care providers.
Proper citation: National Kidney Disease Education Program (RRID:SCR_006527) 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
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
Produce resources to unravel the interface between insulin action, insulin resistance and the genetics of type 2 diabetes including an annotated public database, standardized protocols for gene expression and proteomic analysis, and ultimately diabetes-specific and insulin action-specific DNA chips for investigators in the field. The project aims to identify the sets of the genes involved in insulin action and the predisposition to type 2 diabetes, as well as the secondary changes in gene expression that occur in response to the metabolic abnormalities present in diabetes. There are five major and one pilot project involving human and rodent tissues that are designed to: * Create a database of the genes expressed in insulin-responsive tissues, as well as accessible tissues, that are regulated by insulin, insulin resistance and diabetes. * Assess levels and patterns of gene expression in each tissue before and after insulin stimulation in normal and genetically-modified rodents; normal, insulin resistant and diabetic humans, and in cultured and freshly isolated cell models. * Correlate the level and patterns of expression at the mRNA and/or protein level with the genetic and metabolic phenotype of the animal or cell. * Generate genomic sequence from a panel of humans with type 2 diabetes focusing on the genes most highly regulated by insulin and diabetes to determine the range of sequence and expression variation in these genes and the proteins they encode, which might affect the risk of diabetes or insulin resistance. The DGAP project will define: * the normal anatomy of gene expression, i.e. basal levels of expression and response to insulin. * the morbid anatomy of gene expression, i.e., the impact of diabetes on expression patterns and the insulin response. * the extent to which genetic variability might contribute to the alterations in expression or to diabetes itself.
Proper citation: DGAP (RRID:SCR_003036) Copy
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
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
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
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
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.
