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http://www.diabetes-translation.org

Centers that are part of an integrated program whose cores support and enhance diabetes type II translation research. The CDTRs aim to enhance the efficiency, productivity, effectiveness and multidisciplinary nature of diabetes translation research.

Proper citation: Centers for Diabetes Translation Research (RRID:SCR_015149) Copy   

•   Source: SciCrunch Registry

http://globalprojects.ucsf.edu/project/novel-small-molecule-therapies-cystic-fibrosis

Research center that focuses on developing novel therapies for cystic fibrosis, enhancing research projects examining the mechanisms of the disease, and developing new small-molecule therapies that can be translated into the clinic.

Proper citation: Cystic Fibrosis Center - University of California San Francisco (RRID:SCR_015398) Copy   

•   Source: SciCrunch Registry

http://www.uchicagoddrcc.org

Center whose goals include fostering collaboration among basic and clinical investigators, facilitating the use of new technologies in the study of treatment of digestive diseases, and providing education and training for improved treatment and diagnosis.

Proper citation: University of Chicago Digestive Diseases Research Core Center (RRID:SCR_015601) Copy   

•   Source: SciCrunch Registry

http://www.bsc.gwu.edu/dpp/index.htmlvdoc

Multicenter clinical research study aimed at discovering whether modest weight loss through dietary changes and increased physical activity or treatment with the oral diabetes drug metformin (Glucophage) could prevent or delay the onset of type 2 diabetes in study participants. At the beginning of the DPP, all 3,234 study participants were overweight and had blood glucose levels higher than normal but not high enough for a diagnosis of diabetesa condition called prediabetes. In addition, 45 percent of the participants were from minority groups-African American, Alaska Native, American Indian, Asian American, Hispanic/Latino, or Pacific Islander-at increased risk of developing diabetes. The DPP found that participants who lost a modest amount of weight through dietary changes and increased physical activity sharply reduced their chances of developing diabetes. Taking metformin also reduced risk, although less dramatically. In the DPP, participants from 27 clinical centers around the United States were randomly divided into different treatment groups. The first group, called the lifestyle intervention group, received intensive training in diet, physical activity, and behavior modification. By eating less fat and fewer calories and exercising for a total of 150 minutes a week, they aimed to lose 7 percent of their body weight and maintain that loss. The second group took 850 mg of metformin twice a day. The third group received placebo pills instead of metformin. The metformin and placebo groups also received information about diet and exercise but no intensive motivational counseling. A fourth group was treated with the drug troglitazone (Rezulin), but this part of the study was discontinued after researchers discovered that troglitazone can cause serious liver damage. The participants in this group were followed but not included as one of the intervention groups. In the years since the DPP was completed, further analyses of DPP data continue to yield important insights into the value of lifestyle changes in helping people prevent type 2 diabetes and associated conditions. For example, one analysis confirmed that DPP participants carrying two copies of a gene variant, or mutation, that significantly increased their risk of developing diabetes benefited from lifestyle changes as much as or more than those without the gene variant. Another analysis found that weight loss was the main predictor of reduced risk for developing diabetes in DPP lifestyle intervention group participants. The authors concluded that diabetes risk reduction efforts should focus on weight loss, which is helped by increased exercise.

Proper citation: Diabetes Prevention Program (RRID:SCR_001501) Copy   

•   Source: SciCrunch Registry

https://anvilproject.org/

Portal to facilitate integration and computing on and across large datasets generated by NHGRI programs, as well as initiatives funded by National Institutes of Health or by other agencies that support human genomics research. Resource for genomic scientific community, that leverages cloud based infrastructure for democratizing genomic data access, sharing and computing across large genomic, and genomic related data sets. Component of federated data ecosystem, and is expected to collaborate and integrate with other genomic data resources through adoption of FAIR (Findable, Accessible, Interoperable, Reusable) principles, as their specifications emerge from scientific community. Will provide collaborative environment, where datasets and analysis workflows can be shared within consortium and be prepared for public release to broad scientific community through AnVIL user interfaces.

Proper citation: Analysis, Visualization, and Informatics Lab-space (AnVIL) (RRID:SCR_017469) Copy   

•   Source: SciCrunch Registry

https://www.beilstein-strenda-db.org/strenda/

Storage and search platform supported by Beilstein-Institut that incorporates STRENDA Guidelines. For authors who prepare manuscript containing functional enzymology data, STRENDA DB provides means to ensure that data sets are complete and valid before submitting them to journal.

Proper citation: STRENDA (RRID:SCR_017422) Copy   

•   Source: SciCrunch Registry

http://idr.openmicroscopy.org/about/

Public repository of reference image datasets from published scientific studies. Platform for publishing, mining and integrating bioimaging data, following FAIR principles and Euro-BioImaging/ELIXIR imaging strategy using OMERO and Bio-Formats open source software built by Open Microscopy Environment. Deployed on OpenStack cloud running on EMBL-EBI’s Embassy resource, it includes image data linked to independent studies from genetic, RNAi, chemical, localisation and geographic high content screens, super resolution microscopy, and digital pathology.

Proper citation: Image Data Resource (IDR) (RRID:SCR_017421) Copy   

•   Source: SciCrunch Registry

https://www.smir.ch/

Medical image repository to store medical research data.

Proper citation: SICAS Medical Image Repository (RRID:SCR_017420) Copy   

•   Source: SciCrunch Registry

https://www.ebi.ac.uk/eva/

Open access database of all types of genetic variation data from all species. Users can download data from any study, or submit their own data to archive. You can also query all variants by study, gene, chromosomal location or dbSNP identifier using our Variant Browser.

Proper citation: European Variation Archive (EVA) (RRID:SCR_017425) Copy   

•   Source: SciCrunch Registry

http://pcddb.cryst.bbk.ac.uk/home.php

Public repository for archiving circular dichroism spectroscopic data and associated bioinformatics and experimental metadata. For authors to deposit experimental data as well as detailed information on methods and calculations associated with published work. Includes links for each entry to bioinformatics databases. Data are freely available to accessors either as single files or as complete data bank downloads.

Proper citation: Protein Circular Dichroism Data Bank (PCDDB) (RRID:SCR_017428) Copy   

•   Source: SciCrunch Registry

http://www.immunexpresso.org

Software tool as text-mining engine that structures and standardizes knowledge of immune intercellular communication. Knowledgebase contains interactions and separate mentions of cells or cytokines in context of thousands of diseases. Intercellular interactions were text-mined from all available PubMed abstracts across disease conditions.

Proper citation: immuneXpresso (RRID:SCR_017578) Copy   

•   Source: SciCrunch Registry

http://www2.bsc.gwu.edu/bsc/oneproj.php?pkey=28

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Collect, store, and distribute genetic samples from cases and controls of type 1 diabetes and diabetic nephropathy for investigator-driven research into the genetic basis of diabetic nephropathy. As the risk of kidney complications in type 1 diabetes appears to have a considerable genetic component, this study assembled a large data resource for researchers attempting to identify causative genetic variants. The types of data collected allowed traditional case-control testing, a rapid and often powerful approach, and family-based analysis, a robust approach that is not influenced by population substructure.

Proper citation: Genetics of Kidneys in Diabetes (RRID:SCR_000133) Copy   

•   Source: SciCrunch Registry

http://www2.niddk.nih.gov/NR/rdonlyres/8E99FCF4-8A92-43EE-8E47-5B70D634938A/0/AUABPH.pdf

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Adapted from the American Urology Association Symptom Score for Benign Prostatic Hyperplasia, this chart will assist physicians, researchers, and patients in assessing the severity of the problem.

Proper citation: Symptom Score for Benign Prostatic Hyperplasia (RRID:SCR_000127) 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://www.signalingpathways.org/ominer/query.jsf

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on February 25, 2022.Software tool as knowledge environment resource that accrues, develops, and communicates information that advances understanding of structure, function, and role in disease of nuclear receptors (NRs) and coregulators. It specifically seeks to elucidate roles played by NRs and coregulators in metabolism and development of metabolic disorders. Includes large validated data sets, access to reagents, new findings, library of annotated prior publications in field, and journal covering reviews and techniques.As of March 20, 2020, NURSA is succeeded by the Signaling Pathways Project (SPP).

Proper citation: Nuclear Receptor Signaling Atlas (RRID:SCR_003287) Copy   

•   Source: SciCrunch Registry

http://zgc.nci.nih.gov/

Part of zebrafish genome project. ZGC project to produce cDNA libraries, clones and sequences to provide complete set of full-length (open reading frame) sequences and cDNA clones of expressed genes for zebrafish. All ZGC sequences are deposited in GenBank and clones can be purchased from distributors of IMAGE consortium. With conclusion of ZGC project in September 2008, GenBank records of ZGC sequences will be frozen, without further updates. Since definition of what constitutes full-length coding region for some of genes and transcripts for which we have ZGC clones will likely change in future, users planning to order ZGC clones will need to monitor for these changes. Users can make use of genome browsers and gene-specific databases, such as UCSC Genome browser, NCBI's Map Viewer, and Entrez Gene, to view relevant regions of genome (browsers) or gene-related information (Entrez Gene).

Proper citation: Zebrafish Gene Collection (RRID:SCR_007054) Copy   

•   Source: SciCrunch Registry

http://www.mousephenotype.org/

Center that produces knockout mice and carries out high-throughput phenotyping of each line in order to determine function of every gene in mouse genome. These mice will be preserved in repositories and made available to scientific community representing valuable resource for basic scientific research as well as generating new models for human diseases.

Proper citation: International Mouse Phenotyping Consortium (IMPC) (RRID:SCR_006158) Copy   

•   Source: SciCrunch Registry

http://www.cristudy.org/Chronic-Kidney-Disease/Chronic-Renal-Insufficiency-Cohort-Study/

A prospective observational national cohort study poised to make fundamental insights into the epidemiology, management, and outcomes of chronic kidney disease (CKD) in adults with intended long-term follow up. The major goals of the CRIC Study are to answer two important questions: * Why does kidney disease get worse in some people, but not in others? * Why do persons with kidney disease commonly experience heart disease and stroke? The CRIC Scientific and Data Coordinating Center at Penn receives data and provides ongoing support for a number of Ancillary Studies approved by the CRIC Cohort utilizing both data collected about CRIC study participants as well as their biological samples. The CRIC Study has enrolled over 3900 men and women with CKD from 13 recruitment sites throughout the country. Following this group of individuals over the past 10 years has contributed to the knowledge of kidney disease, its treatment, and preventing its complications. The NIDDKwill be extending the study for an additional 5 years, through 2018. An extensive set of study data is collected from CRIC Study participants. With varying frequency, data are collected in the domains of medical history, physical measures, psychometrics and behaviors, biomarkers, genomics/metabolomics, as well as renal, cardiovascular and other outcomes. Measurements include creatinine clearance and iothalamate measured glomerular filtration rate. Cardiovascular measures include blood pressure, ECG, ABI, ECHO, and EBCT. Clinical CV outcomes include MI, ischemic heart disease-related death, acute coronary syndromes, congestive heart failure, cerebrovascular disease, peripheral vascular disease, and composite outcomes. The CRIC Study has delivered in excess of 150,000 bio-samples and a dataset characterizing all 3939 CRIC participants at the time of study entry to the NIDDKnational repository. The CRIC Study will also be delivering a dataset to NCBI''''s Database for Genotypes and Phenotypes.

Proper citation: Chronic Renal Insufficiency Cohort Study (RRID:SCR_009016) Copy   

•   Source: SciCrunch Registry

https://hddc.hms.harvard.edu/gnotobiotics-microbiology-and-metagenomics

Core facility that assists investigators evaluating host microbiota and its role in normal physiology and disease. It includes a number of resources for groups studying the role of the microbiota in human health and disease.

Proper citation: Harvard Digestive Diseases Center Biomedical CORE D: Gnotobiotic Mice, Microbiology and Metagenomics (RRID:SCR_012319) Copy   

•   Source: SciCrunch Registry

http://sph.unc.edu/norc/norc-diet-and-physical-activity-core/

Core that provides diet, physical activity, or statistical analysis consultation, as well as consultation for the design and development of diet and physical activity data collection protocols.

Proper citation: University of North Carolina at Chapel Hill Nutrition and Obesity Research Center Diet and Physical Activity Core (RRID:SCR_012588) Copy   

•   Source: SciCrunch Registry