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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://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://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.

Proper citation: TopDom (RRID:SCR_016964) 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://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

http://grantome.com/grant/NIH/U01-DK099919-04S1

Consortium to design and conduct pilot and feasibility studies of novel therapies to reduce morbidity and mortality for patients treated with maintenance hemodialysis. Data Coordinating Center (DCC) for consortium provides scientific expertise and operational support for pilot studies that will be conducted at HDPSC Participating Clinical Centers. Data Coordinating Center for Hemodialysis Pilot Studies Consortium.

Proper citation: Hemodialysis Pilot Studies Consortium (RRID:SCR_017468) Copy   

•   Source: SciCrunch Registry

http://toppgene.cchmc.org/

ToppGene Suite is a one-stop portal for gene list enrichment analysis and candidate gene prioritization based on functional annotations and protein interactions network. ToppGene Suite is a one-stop portal for (i) gene list functional enrichment, (ii) candidate gene prioritization using either functional annotations or network analysis and (iii) identification and prioritization of novel disease candidate genes in the interactome. Functional annotation-based disease candidate gene prioritization uses a fuzzy-based similarity measure to compute the similarity between any two genes based on semantic annotations. The similarity scores from individual features are combined into an overall score using statistical meta-analysis.

Proper citation: ToppGene Suite (RRID:SCR_005726) Copy   

•   Source: SciCrunch Registry

http://www.jneurosci.org/supplemental/18/12/4570/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 29, 2013. Supplemental data for the paper Changes in mitochondrial function resulting from synaptic activity in the rat hippocampal slice, by Vytautas P. Bindokas, Chong C. Lee, William F. Colmers, and Richard J. Miller that appears in the Journal of Neuroscience June 15, 1998. You can view digital movies of changes in fluorescence intensity by clicking on the title of interest.

Proper citation: Hippocampal Slice Wave Animations (RRID:SCR_008372) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/mpg/grail/

A tool to examine relationships between genes in different disease associated loci. Given several genomic regions or SNPs associated with a particular phenotype or disease, GRAIL looks for similarities in the published scientific text among the associated genes. As input, users can upload either (1) SNPs that have emerged from a genome-wide association study or (2) genomic regions that have emerged from a linkage scan or are associated common or rare copy number variants. SNPs should be listed according to their rs#''s and must be listed in HapMap. Genomic Regions are specified by a user-defined identifier, the chromosome that it is located on, and the start and end base-pair positions for the region. Grail can take two sets of inputs - Query regions and Seed regions. Seed regions are definitely associated SNPs or genomic regions, and Query regions are those regions that the user is attempting to evaluate agains them. In many applications the two sets are identical. Based on textual relationships between genes, GRAIL assigns a p-value to each region suggesting its degree of functional connectivity, and picks the best candidate gene. GRAIL is developed by Soumya Raychaudhuri in the labs of David Altshuler and Mark Daly at the Center for Human Genetic Research of Massachusetts General Hospital and Harvard Medical School, and the Broad Institute. GRAIL is described in manuscript, currently in preparation.

Proper citation: Gene Relationships Across Implicated Loci (RRID:SCR_008537) Copy   

•   Source: SciCrunch Registry

http://www.mmpc.org

The mission is to advance medical and biological research by providing the scientific community with standardized, high quality metabolic and physiologic phenotyping services for mouse models of diabetes, diabetic complications, obesity and related disorders.

Proper citation: National Mouse Metabolic Phenotyping Centers (RRID:SCR_008997) Copy   

•   Source: SciCrunch Registry

http://www.cori.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 5, 2022. Endoscopic Reporting Software, aggregated and individual research data and tailor-made services aimed to advance the overall practice of endoscopy. It was developed to study outcomes of gastrointestinal (GI) endoscopic procedures in real life settings, using data obtained from the CORI Endoscopic Reporting Software or from other endoscopic reporting software. Practice sites include hospitals, ambulatory care centers, private practices, universities, and Veteran''''s hospitals (VA''''s). The CORI v4 Endoscopic Reporting Software is a specialty Electronic Health Record used to document endoscopic procedures and provide reporting services to your practice. Data from participating providers is also sent to a central data repository to become part of the National Endoscopic Database (NED), which now contains data from over 2.7 million GI procedures. The CORI v4 Endoscopic Reporting Software offers significant benefits for participating practices, providers and patients, as well as for everyone who benefits from CORI''''s research efforts. You may actively participate in research with CORI. If you have ideas for research using the NED, their research team can help you evaluate those ideas, collect and analyze the data. In addition, you may choose to participate in one of the prospective research projects conducted by CORI research staff.

Proper citation: Clinical Outcomes Research Initiative (RRID:SCR_009010) Copy   

•   Source: SciCrunch Registry

http://www.cidr.jhmi.edu/

Next generation sequencing and genotyping services provided to investigators working to discover genes that contribute to disease. On-site statistical geneticists provide insight into analysis issues as they relate to study design, data production and quality control. In addition, CIDR has a consulting agreement with the University of Washington Genetics Coordinating Center (GCC) to provide statistical and analytical support, most predominantly in the areas of GWAS data cleaning and methods development. Completed studies encompass over 175 phenotypes across 530 projects and 620,000 samples. The impact is evidenced by over 380 peer-reviewed papers published in 100 journals. Three pathways exist to access the CIDR genotyping facility: * NIH CIDR Program: The CIDR contract is funded by 14 NIH Institutes and provides genotyping and statistical genetic services to investigators approved for access through competitive peer review. An application is required for projects supported by the NIH CIDR Program. * The HTS Facility: The High Throughput Sequencing Facility, part of the Johns Hopkins Genetic Resources Core Facility, provides next generation sequencing services to internal JHU investigators and external scientists on a fee-for-service basis. * The JHU SNP Center: The SNP Center, part of the Johns Hopkins Genetic Resources Core Facility, provides genotyping to internal JHU investigators and external scientists on a fee-for-service basis. Data computation service is included to cover the statistical genetics services provided for investigators seeking to identify genes that contribute to human disease. Human Genotyping Services include SNP Genome Wide Association Studies, SNP Linkage Scans, Custom SNP Studies, Cancer Panel, MHC Panels, and Methylation Profiling. Mouse Genotyping Services include SNP Scans and Custom SNP Studies.

Proper citation: Center for Inherited Disease Research (RRID:SCR_007339) Copy   

•   Source: SciCrunch Registry

http://t1dbase.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 26,2019. In October 2016, T1DBase has merged with its sister site ImmunoBase (https://immunobase.org). Documented on March 2020, ImmunoBase ownership has been transferred to Open Targets (https://www.opentargets.org). Results for all studies can be explored using Open Targets Genetics (https://genetics.opentargets.org). Database focused on genetics and genomics of type 1 diabetes susceptibility providing a curated and integrated set of datasets and tools, across multiple species, to support and promote research in this area. The current data scope includes annotated genomic sequences for suspected T1D susceptibility regions; genetic data; microarray data; and global datasets, generally from the literature, that are useful for genetics and systems biology studies. The site also includes software tools for analyzing the data.

Proper citation: T1DBase (RRID:SCR_007959) Copy   

•   Source: SciCrunch Registry

http://www2.niddk.nih.gov/Research/Resources/ObesityResources.htm

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 23, 2017. This website contains resources for obesity researchers including: Obesity Databases, Registries and Information; Obesity Multicenter Clinical Research; Obesity Basic Research Networks; Obesity Reagents; Obesity Services; Obesity Standardization Programs; Obesity Tissues, Cells, Animals; Obesity Useful Tools.

Proper citation: NIDDK- National Institute of Diabetes and Digestive and Kidney Diseases Obesity Resources (RRID:SCR_003074) Copy   

•   Source: SciCrunch Registry

http://www.mybiosoftware.com/population-genetics/332

A tool for SNP Search and downloading with local management. It also offers flanking sequence downloading and automatic SNP filtering. It requires Windows and .NET Framework.

Proper citation: SNPHunter (RRID:SCR_002968) Copy   

•   Source: SciCrunch Registry