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https://nih-lurn.org/

A research consortium with the long term goal of developing and testing measurement tools to describe symptoms of lower urinary tract dysfunction (LUTD) in women and men. The group plans to study targeted populations of patients with LUTD in order to expand our understanding of the causes of symptoms and common ways that symptoms change over time. The researchers will also collect biosamples from patients for current and future study of LUTD.

Proper citation: Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) (RRID:SCR_014378) Copy   

•   Source: SciCrunch Registry

https://medschool.cuanschutz.edu/diabetes-research-center

Center to facilitate diabetes research at University of Colorado by integrating interdisciplinary basic, translational, and clinical diabetes research base; providing infrastructure and resources that are indispensable for continued discovery and progress towards diabetes research and developing improved prediction and disease prevention;providing P&F and enrichment programs to support DRC investigators and their trainees, and recruit new and young investigators into diabetes research.

Proper citation: University of Colorado Diabetes Research Center (RRID:SCR_022897) Copy   

•   Source: SciCrunch Registry

https://ncdiabetesresearch.org/

Interactive regional diabetes research community across four premiere research institutions in North Carolina, who currently garner over $70 million annually for support of their diabetes research: Duke University (Duke), The University of North Carolina at Chapel Hill (UNC), Wake Forest School of Medicine (WF), and North Carolina A&T State University (NC A&T State). NCDRC supports Research Cores that represent unique strengths at each institution.

Proper citation: North Carolina Diabetes Research Center (RRID:SCR_022896) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6301786/

Device to control spatial and temporal variations in oxygen tensions to better replicate in vivo biology. Consists of three parallel connected tissue chambers and oxygen scavenger channel placed adjacent to these tissue chambers. Provides consistent control of spatial and temporal oxygen gradients in tissue microenvironment and can be used to investigate important oxygen dependent biological processes present in cancer, ischemic heart disease, and wound healing.

Proper citation: Microfluidic device to attain high spatial and temporal control of oxygen (RRID:SCR_017131) Copy   

•   Source: SciCrunch Registry

http://icr.coh.org/

Group of 10 academic laboratories provide pancreatic islets of cGMP-quality to eligible investigators for use in FDA approved, IRB-approved transplantation protocols in which isolated human islets are transplanted into qualified patients afflicted with type 1 diabetes mellitus; optimize the harvest, purification, function, storage, and shipment of islets while developing tests that characterize the quality and predict the effectiveness of islets transplanted into patients with diabetes mellitus; and provide pancreatic islets for basic science studies. The centers are electronically linked through an Administrative and Bioinformatics Coordinating Center (ABCC). The ABCC manages a system with objectively defined criteria that establishes the order of priority for islet distribution. It also provides database and other informatics to track the utilization of pancreata and all distributed clinical grade islets for transplant and basic research, and supports the Islet Cell Resource Centers Consortium so that the research community has a single entry point to the program. Qualified researchers from domestic institutions may request islets by submitting a written application to the director of the ABCC. The ICRs will distribute Islets as appropriate for either clinical or basic science protocol use to eligible investigators who have received a favorable review and subsequent approval by the ICR Steering Committee (SC). The Administrative and Bioinformatics Coordinating Center (ABCC) manages the distribution according to a priority list. The ABCC will give preference to investigators who have peer-reviewed, NIH-funded research support.

Proper citation: Islet Cell Resource Centers (RRID:SCR_002806) Copy   

•   Source: SciCrunch Registry

http://www.betacell.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented on August 1, 2015. Consortium that aims to facilitate interdisciplinary collaborations to advance the understanding of pancreatic islet development and function, with the goal of developing innovative therapies to correct the loss of beta cell mass in diabetes, including cell reprogramming, regeneration and replacement. They are responsible for collaboratively generating the necessary reagents, mouse strains, antibodies, assays, protocols, technologies and validation assays that are beyond the scope of any single research effort. The scientific goals for the BCBC are to: * Use cues from pancreatic development to directly differentiate pancreatic beta cells and islets from stem / progenitor cells for use in cell-replacement therapies for diabetes, * Determine how to stimulate beta cell regeneration in the adult pancreas as a basis for improving beta cell mass in diabetic patients, * Determine how to reprogram progenitor / adult cells into pancreatic beta-cells both in-vitro and in-vivo as a mean for developing cell-replacement therapies for diabetes, and * Investigate the progression of human type-1 diabetes using patient-derived cells and tissues transplanted in humanized mouse models. Many of the BCBC investigator-initiated projects involve reagent-generating activities that will benefit the larger scientific community. The combination of programs and activities should accelerate the pace of major new discoveries and progress within the field of beta cell biology.

Proper citation: Beta Cell Biology Consortium (RRID:SCR_005136) Copy   

•   Source: SciCrunch Registry

https://www.ibdgc.org/

Repository of biospecimen and phenotype data collected from Crohn's disease and ulcerative colitis cases and controls recruited at six sites throughout North America that are available to the scientific community. Phenotyping is performed using a standardized protocol, and lymphoblastoid cell lines are established for each subject. Phenotype data for each subject are collected by the Consortium's Data Coordinating Center (DCC), and phenotype data for all subjects with DNA samples are available. The resulting DNA samples have already been utilized by the Consortium to complete various association studies, including genome-wide association studies using dense genotyping arrays. Researchers can obtain DNA samples and phenotype, genotype, and pedigree data through the Data Repository. GWAS data must be requested through dbGAP. The IBDGC is involved with independent genetic research studies and actively works with members of the IBD and genetic communities on collaborative projects. They are also members of the International IBD Genetics Consortium. Phenotype Tools: The Consortium Phenotype Committee, led by Dr. Hillary Steinhart designed and validated paper forms to collect extensive phenotype data on Crohn's Disease and ulcerative colitis. Consortium phenotype tools are available for use by non-Consortium members.

Proper citation: NIDDK Inflammatory Bowel Disease Genetics Consortium (RRID:SCR_001461) Copy   

•   Source: SciCrunch Registry

https://www.ohsu.edu/custom/library/digital-collections/projectionmap

Data set of thalamo-centric mesoscopic projection maps to the cortex and striatum. The maps are established through two-color, viral (rAAV)-based tracing images and high throughout imaging.

Proper citation: Mouse Thalamic Projectome Dataset (RRID:SCR_015702) Copy   

•   Source: SciCrunch Registry

https://pypi.org/project/pmlb/

Python wrapper for Penn Machine Learning Benchmark data repository. Large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms. Part of PyPI https://pypi.org/

Proper citation: Penn machine learning benchmark repository (RRID:SCR_017138) Copy   

•   Source: SciCrunch Registry

http://www.gudmap.org/Resources/Ontologies.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. A high-resolution ontology has been developed by members of the GUDMAP consortium to describe the subcompartments of the developing murine genitourinary tract. This ontology incorporates what can be defined histologically and begins to encompass other structures and cell types already identified at the molecular level. The GUDMAP ontology encompasses Theiler stage (TS) 17-27 of development as well as the sexually mature adult. It has been written as a partonomic, text-based, hierarchical ontology that, for the embryological stages, has been developed as a high-resolution expansion of the existing Edinburgh Mouse Atlas Project (EMAP) ontology. It also includes group terms for well-characterized structural and/or functional units comprising several sub-structures, such as the nephron and juxtaglomerular complex. Each term has been assigned a unique identification number. Synonyms have been used to improve the success of query searching and maintain wherever possible existing EMAP terms relating to this organ system.

Proper citation: GUDMAP Ontology (RRID:SCR_002637) Copy   

•   Source: SciCrunch Registry

https://github.com/SciCrunch/Antibody-Watch

Text mining antibody specificity from literature. Helps researchers identify potential problems with antibody specificity. By mining the scientific literature and linking findings to Research Resource Identifiers (RRIDs), it provides alerts on antibodies that may yield unreliable results, supporting reproducibility in biomedical research.

Proper citation: Antibody Watch (RRID:SCR_027424) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://digestive.niddk.nih.gov/statistics/statistics.aspx

A collection of statistics about specific digestive diseases, including prevalence, mortality, care delivery and cost.

Proper citation: Digestive Diseases Statistics for the United States (RRID:SCR_006703) Copy   

•   Source: SciCrunch Registry

https://pancreatlas.org/

Collection of human pancreas data and images. Platform to share data from human pancreas samples. Houses reference datasets from human pancreas samples, achieved through generosity of organ donors and their families.

Proper citation: Pancreatlas (RRID:SCR_018567) Copy   

•   Source: SciCrunch Registry

https://gitlab.com/rosen-lab/white-adipose-atlas

Single cell atlas of human and mouse white adipose tissue.

Proper citation: White Adipose Atlas (RRID:SCR_023625) Copy   

•   Source: SciCrunch Registry

http://www.utsouthwestern.edu/labs/acute-liver/

Clinical research network for gathering prospective data and bio-samples on acute liver failure in adults since 1998. Clinical histories and laboratory and outcome data are available. Sample types include serum, plasma, urine, DNA, and liver tissue.

Proper citation: Acute Liver Failure Study Group (RRID:SCR_001463) Copy   

•   Source: SciCrunch Registry

https://github.com/FunctionalUrology/MLme

Software toolkit for Machine Learning Driven Data Analysis. Simplifies machine learning for data exploration, visualization and analysis.

Proper citation: Machine Learning Made Easy (RRID:SCR_024439) Copy   

•   Source: SciCrunch Registry

https://huttenhower.sph.harvard.edu/picrust/

Software for predicting functional abundances based only on marker gene sequences.Used for prediction of metagenome functions. Contains updated and larger database of gene families and reference genomes, provides interoperability with any operational taxonomic unit (OTU)-picking or denoising algorithm, and enables phenotype predictions. Allows addition of custom reference databases.

Proper citation: PICRUSt2 (RRID:SCR_022647) Copy   

•   Source: SciCrunch Registry

https://picrust.github.io/picrust/

Software package to predict metagenome functional content from marker gene (e.g., 16S rRNA) surveys and full genomes. Used to predict which gene families are present and then combines gene families to estimate the composite metagenome.

Proper citation: PICRUSt (RRID:SCR_016855) Copy   

•   Source: SciCrunch Registry

https://github.com/compbiolabucf/PTNet

Graph based learning model for protein expression estimation by considering miRNA-mRNA interactions. Estimates protein levels by considering miRNA-mRNA interaction network, mRNA expression and miRNA expression.

Proper citation: PTNet (RRID:SCR_022975) Copy   

•   Source: SciCrunch Registry