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https://www.med.upenn.edu/idom/

NIDDK center that serves diabetes-oriented investigators from University of Pennsylvania as well as additional institutions from the mid-Atlantic region. The Penn DRC represents many basic science and clinical departments at Penn and the other institutions, and supports research in diabetes and obesity via Scientific Cores, a Pilot and Feasibility Grant Program, and a series of seminars, retreats, and other academic enrichment activities.

Proper citation: University of Pennsylvania Diabetes Research Center (RRID:SCR_015732) Copy   

•   Source: SciCrunch Registry

https://hirnetwork.org/consortium/ctar

Consortium that is an independent research initiative of the Human Research Information Network (HIRN). It is investigating methods to increase or maintain functional beta cell mass in T1D through targeted manipulation of islet plasticity or engineered protection of beta cells from immune-mediated destruction.

Proper citation: HIRN Consortium on Targeting and Regeneration (RRID:SCR_016201) Copy   

•   Source: SciCrunch Registry

http://bioplex.hms.harvard.edu/

Database of cell lines with each expressing a tagged version of a protein from the ORFeome collection. The overarching project goal is to determine protein interactions for every member of the collection.

Proper citation: BioPlex (RRID:SCR_016144) Copy   

•   Source: SciCrunch Registry

https://hirnetwork.org/consortium/chib

Consortium that is an independent research initiative of the Human Research Information Network (HIRN). It is combining advances in beta cell biology and cell biology with tissue engineering technologies to develop microdevices that support functional human islets.

Proper citation: HIRN Consortium on Human Islet Biomimetics (RRID:SCR_016199) Copy   

•   Source: SciCrunch Registry

https://hirnetwork.org/consortium/cbds

Consortium that is an independent research initiative of the Human Research Information Network (HIRN). It is using human tissues to discover highly specific biomarkers of beta cell injury in asymptomatic T1D and developing strategies to stop beta cell destruction early in the disease process.

Proper citation: HIRN Consortium on Beta Cell Death and Survival (RRID:SCR_016198) Copy   

•   Source: SciCrunch Registry

https://hirnetwork.org/project/hirncc

Consortium that provides infrastructure to promote communication and collaboration among current and future HIRN participants, facilitating scientific advances and the sharing of data, tools, and reagents among HIRN members and the research community at large.

Proper citation: HIRN Coordinating Center (RRID:SCR_016395) Copy   

•   Source: SciCrunch Registry

http://www.autoimmunitycenters.org/

Nine centers that conduct clinical trials and basic research on new immune-based therapies for autoimmune diseases. This program enhances interactions between scientists and clinicians in order to accelerate the translation of research findings into medical applications. By promoting better coordination and communication, and enabling limited resources to be pooled, ACEs is one of NIAID''''s primary vehicles for both expanding our knowledge and improving our ability to effectively prevent and treat autoimmune diseases. This coordinated approach incorporates key recommendations of the NIH Autoimmune Diseases Research Plan and will ensure progress in identifying new and highly effective therapies for autoimmune diseases. ACEs is advancing the search for effective treatments through: * Diverse Autoimmunity Expertise Medical researchers at ACEs include rheumatologists, neurologists, gastroenterologists, and endocrinologists who are among the elite in their respective fields. * Strong Mechanistic Foundation ACEs augment each clinical trial with extensive basic studies designed to enhance understanding of the mechanisms responsible for tolerance initiation, maintenance, or loss, including the role of cytokines, regulatory T cells, and accessory cells, to name a few. * Streamlined Patient Recruitment The cooperative nature of ACEs helps scientists recruit patients from distinct geographical areas. The rigorous clinical and basic science approach of ACEs helps maintain a high level of treatment and analysis, enabling informative comparisons between patient groups.

Proper citation: Autoimmunity Centers of Excellence (RRID:SCR_006510) Copy   

•   Source: SciCrunch Registry

http://www.nkdep.nih.gov/lab-evaluation/gfr-calculators.shtml

Glomerular Filtration Rate (GFR) calculators to estimate kidney function for adults (MDRD GFR Calculator) and children (Schwartz GFR Calculator). In adults, the recommended equation for estimating glomerular filtration rate (GFR) from serum creatinine is the Modification of Diet in Renal Disease (MDRD) Study equation. The IDMS-traceable version of the MDRD Study equation is used. Currently the best equation for estimating glomerular filtration rate (GFR) from serum creatinine in children is the Bedside Schwartz equation for use with creatinine methods with calibration traceable to IDMS. Using the original Schwartz equation with a creatinine value from a method with calibration traceable to IDMS will overestimate GFR.

Proper citation: Glomerular Filtration Rate Calculators (RRID:SCR_006443) Copy   

•   Source: SciCrunch Registry

http://www.nkdep.nih.gov/lab-evaluation/gfr/creatinine-standardization.shtml

Standard specification to reduce inter-laboratory variation in creatinine assay calibration and therefore enable more accurate estimates of glomerular filtration rate (eGFR). Created by NKDEP''''s Laboratory Working Group in collaboration with the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) and the European Communities Confederation of Clinical Chemistry (now called the European Federation of Clinical Chemistry and Laboratory Medicine), the effort is part of a larger NKDEP initiative to help health care providers better identify and treat chronic kidney disease in order to prevent or delay kidney failure and improve patient outcomes. Recommendations are intended for the USA and other countries or regions that have largely completed standardization of creatinine calibration to be traceable to an isotope dilution mass spectrometry (IDMS) reference measurement procedure. The program''''s focus is to facilitate the sharing of information to assist in vitro diagnostic manufacturers, clinical laboratories, and others in the laboratory community with calibrating their serum creatinine measurement procedures to be traceable to isotope dilution mass spectrometry (IDMS). The program also supports manufacturers'''' efforts to encourage their customers in the laboratory to coordinate use of standardized creatinine methods with implementation of a revised GFR estimating equation appropriate for use with standardized creatinine methods. Communication resources and other information for various segments of the laboratory community are available in the Creatinine Standardization Recommendations section of the website. Also available is a protocol for calibrating creatinine measurements using whole blood devices. The National Institute for Standards and Technology (NIST) released a standard reference material (SRM 967 Creatinine in Frozen Human Serum) for use in establishing calibrations for routine creatinine measurement procedures. SRM 967 was validated to be commutable with native serum samples for many routine creatinine procedures and is useful to establish or verify traceability to an IDMS reference measurement procedure. Establishing calibrations for serum creatinine methods using SRM 967 not only provides a mechanism for ensuring more accurate measurement of serum creatinine, but also enables more accurate estimates of GFR. For clinical laboratories interested in independently checking the calibration supplied by their creatinine reagent suppliers/manufacturers, periodic measurement of NIST SRM 967 should be considered for inclusion in the lab''''s internal quality assurance program. To learn more about SRM 967, including how to purchase it, visit the NIST website, https://www-s.nist.gov/srmors/quickSearch.cfm

Proper citation: Creatinine Standardization Program (RRID:SCR_006441) Copy   

•   Source: SciCrunch Registry

http://www.usrds.org/

Annual report, standard analysis files and an online query system from the national data registry on the end-stage renal disease (ESRD) population in the U.S., including treatments and outcomes. The Annual Data Report is divided into two parts. The Atlas section displays data using graphs and charts. Specific chapters address trends in ESRD patient populations, quality of ESRD care, kidney transplantation outcomes, costs of ESRD care, Healthy People 2010 objectives, chronic kidney disease, pediatric ESRD, and cardiovascular disease special studies. The Reference Tables are devoted entirely to the ESRD population. The RenDER (Renal Data Extraction and Referencing) online data query system allows users to build data tables and maps for the ESRD population. National, state, and county level data are available. USRDS staff collaborates with members of Centers for Medicare & Medicaid Services (CMS), the United Network for Organ Sharing (UNOS), and the ESRD networks, sharing datasets and actively working to improve the accuracy of ESRD patient information.

Proper citation: United States Renal Data System (RRID:SCR_006699) 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

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   

•   Source: SciCrunch Registry

https://cm.jefferson.edu/rna22/

Software tool as a pattern based algorithm for detecting microRNA binding sites and their corresponding microRNA and mRNA complexes. Allows interactive exploration and visualization of miRNA target predictions. Permits link-out to external expression repositories and databases.

Proper citation: RNA22 (RRID:SCR_016507) Copy   

•   Source: SciCrunch Registry

https://plusconsortium.umn.edu

Research consortium from many different fields to plan, perform and analyze the studies that are needed to help researchers conduct future prevention and intervention for Lower Urinary Tract Symptoms (LUTS) in women.

Proper citation: Prevention of Lower Urinary Tract Symptoms (RRID:SCR_016923) Copy   

•   Source: SciCrunch Registry

https://kpmp.org

Project to ethically obtain and evaluate human kidney biopsies from participants with Acute Kidney Injury (AKI) or Chronic Kidney Disease (CKD), create a kidney tissue atlas, define disease subgroups, and identify critical cells, pathways, and targets for novel therapies. Used to develop the next generation of software tools to visualize and understand the various components of kidney diseases and to optimize data collection. Multi site collaboration comprised of patients, clinicians, and investigators from across the United States.

Proper citation: Kidney Precision Medicine Project (RRID:SCR_016920) 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

http://zhoulab.usc.edu/TopDom/

Software tool to identify Topological Domains, which are basic builiding blocks of genome structure. Detects topological domains in a linear time., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: TopDom (RRID:SCR_016964) Copy   

•   Source: SciCrunch Registry

https://immunedb.readthedocs.io/en/latest/

Software system for storing and analyzing high throughput B and T cell immune receptor sequencing data. Comprised of web interface and of Python analysis tools to process raw reads for gene usage, infer clones, aggregate data, and run downstream analyses, or in conjunction with other AIRR tools using its import and export features.

Proper citation: ImmuneDB (RRID:SCR_017125) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/CATALYST/

Software R package to provide pipeline for preprocessing of cytometry data, including normalization using bead standards, single cell deconvolution, and bead based compensation.

Proper citation: CATALYST (RRID:SCR_017127) Copy   

•   Source: SciCrunch Registry

https://exrna-atlas.org

Software tool as data and metadata repository of Extracellular RNA Communication Consortium. Atlas includes small RNA sequencing and qPCR derived exRNA profiles from human and mouse biofluids. All RNAseq datasets are processed using version 4 of exceRpt small RNAseq pipeline. Atlas accepts submissions for RNAseq or qPCR data.

Proper citation: exRNA Atlas (RRID:SCR_017221) Copy   

•   Source: SciCrunch Registry