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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

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://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

http://www.uchicagoddrcc.org/research-cores/tissue-engineering-and-cell-models-core

Core that provides services such as a repository for intestinal cell lines, Tissue Engineering Models, experimental materials, and supplies for digestive disease research.

Proper citation: University of Chicago Digestive Diseases Research Core Center Tissue Engineering and Cell Models Core (RRID:SCR_015604) 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

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/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

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

http://sharedresources.fredhutch.org/core-facilities/cceh-administration

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July,27,2022. Core facility that provides scientific and budgetary oversight for all CCEH activities. This includes training programs, high school summer internships, and and pilot and feasibility program for new projects.

Proper citation: Fred Hutchinson Cancer Research Center Co-operative Center for Excellence in Hematology (RRID:SCR_015320) Copy   

•   Source: SciCrunch Registry

http://www.med.umich.edu/mgpc/

Center whose goal is to investigate signal transduction mechanisms regulating homeostasis and GI disorders. Their approach includes studies on genetics and gene regulation, cellular signaling pathways, receptors and ion channels.

Proper citation: University of Michigan Center for Gastrointestinal Research (RRID:SCR_015605) 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://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.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.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

http://www.cure.med.ucla.edu/

Center whose interests and activities encompass several facets of gastrointestinal regulatory physiology and cell biology. It provides an infrastructure to support basic, translational and clinical research and to facilitate interdisciplinary research and training activities in digestive diseases.

Proper citation: CURE - Digestive Diseases Research Center (RRID:SCR_004238) 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