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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
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
Consortium serving the diabetic complications community that sponsors annual meetings in complications-relevant scientific areas, solicits and funds pilot projects in high impact areas of complications research, and provides resources and data including animal models, protocols and methods, validation criteria, reagents and resources, histology, publications and bioinformatics for researchers conducting diabetic complications research.
Proper citation: Diabetic Complications Consortium (RRID:SCR_001415) Copy
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
Ratings or validation data are available for this resource
http://iidp.coh.org/Default.aspx
The goal of the Integrated Islet Distribution Program (IIDP) is to work with the leading islet isolation centers in the U.S. to distribute high quality human islets to the diabetes research community, in order to advance scientific discoveries and translational medicine.
Proper citation: Integrated Islet Distribution Program (IIDP) (RRID:SCR_014387) Copy
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
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
https://maayanlab.cloud/sigcom-lincs
Web server that serves over million gene expression signatures processed, analyzed, and visualized from LINCS, GTEx, and GEO. Data and metadata search engine for gene expression signatures.
Proper citation: SigCom LINCS (RRID:SCR_022275) Copy
https://github.com/zdk123/SpiecEasi
Software R package for microbiome network analysis. Used for inference of microbial ecological networks from amplicon sequencing datasets. Combines data transformations developed for compositional data analysis with graphical model inference framework that assumes underlying ecological association network is sparse.
Proper citation: SpiecEasi (RRID:SCR_022712) Copy
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
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
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
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
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
Resource enables integrative exploration of genetic and epigenetic basis of development of Type 2 Diabetes, together with other associated functional, molecular and clinical data, centered in biology and role of pancreatic beta cells.The gene expression regulatory variation landscape of human pancreatic islets.
Proper citation: TIGER Data Portal (RRID:SCR_023626) Copy
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
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
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
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
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
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
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