Tools   Select Another Resource Report Type

http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) 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

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://clonesearch.jdrfnpod.org/

Database of sequence data generated from high-throughput immunosequencing of the TCR beta chain (TRB) and B cell receptor (BCR) immunoglobulin heavy chain (IGH). This data comes from cells from NPOD donors.

Proper citation: nPOD TCR/BCR Search (RRID:SCR_015851) 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

http://www.uniprot.org/

Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.

Proper citation: UniProt (RRID:SCR_002380) Copy   

•   Source: SciCrunch Registry

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://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://github.com/EpistasisLab/ReBATE

Open source software Python package to compare relief based feature selection algorithms used in data mining. Used for feature selection in any bioinformatics problem with potentially predictive features and target outcome variable, to detect feature interactions without examination of all feature combinations, to detect features involved in heterogeneous patterns of association such as genetic heterogeneity .

Proper citation: ReBATE (RRID:SCR_017139) Copy   

•   Source: SciCrunch Registry

https://github.com/zeyang-shen/maggie

Software Python package for identifying motifs mediating transcription factor binding and function. Links mutations of motif to changes of epigenomic feature without assuming linear relationship.

Proper citation: Motif Alteration Genome wide to Globally Investigate Elements (RRID:SCR_021903) 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.t1diabetes.nih.gov/T1D-PTP/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Investigator access is provided to the established facilities and expertise needed to extend, enhance and validate preclinical studies of promising new therapeutics in cases where additional preclinical testing is needed to validate potential therapies under disease-specific conditions and in multiple animal models before therapeutics can enter the Type 1 Diabetes Rapid Access to Intervention Development (T1D-RAID) development pipeline. The T1D-RAID program provides resources for pre-clinical development of drugs, natural products, and biologics that will be tested as new therapeutics in type 1 diabetes clinical trials. The T1D-RAID program is not currently accepting applications. The T1D-PTP program currently supports two contracts, which are separate from each other and from the T1D-RAID NCI contract resources, to assist in preclinical development of therapeutics for T1D: * Agents to be tested for Preclinical Efficacy in Prevention or Reversal of Type 1 Diabetes in Rodent Models. Type 1 Diabetes Preclinical Testing Program (T1D-PTP) (NOT-DK-09-006) * Needs for Preclinical Efficacy Testing of Promising Agents to Prevent or Reverse Diabetic Complications (NOT-DK-09-009) The T1D-RAID and T1D-PTP are programs intended to remove the most common barriers to progress in identification and development of new therapies for Type 1 Diabetes. The common goal of these programs is to support and provide for the preclinical work necessary to obtain proof of principle establishing that a new molecule or novel approach will be a viable candidate for expanded clinical evaluation.

Proper citation: Type 1 Diabetes Preclinical Testing Program (RRID:SCR_006861) Copy   

•   Source: SciCrunch Registry

http://www.citisletstudy.org/

Network of clinical centers and a data coordinating center established to conduct studies of islet transplantation in patients with type 1 diabetes.

Proper citation: Clinical Islet Transplantation Consortium (CITC) (RRID:SCR_014385) 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.tarp.nih.gov/

Trans-NIH program encouraging and facilitating the study of the underlying mechanisms controlling blood vessel growth and development. Other aims include: to identify specific targets and to develop therapeutics against pathologic angiogenesis in order to reduce the morbidity due to abnormal blood vessel proliferation in a variety of disease states; to better understand the process of angiogenesis and vascularization to improve states of decreased vascularization; to encourage and facilitate the study of the processes of lymphangiogenesis; and to achieve these goals through a multidisciplinary approach, bringing together investigators with varied backgrounds and varied interests.

Proper citation: Trans-Institute Angiogenesis Research Program (RRID:SCR_000384) 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