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http://www.diabetesgenome.org

Produce resources to unravel the interface between insulin action, insulin resistance and the genetics of type 2 diabetes including an annotated public database, standardized protocols for gene expression and proteomic analysis, and ultimately diabetes-specific and insulin action-specific DNA chips for investigators in the field. The project aims to identify the sets of the genes involved in insulin action and the predisposition to type 2 diabetes, as well as the secondary changes in gene expression that occur in response to the metabolic abnormalities present in diabetes. There are five major and one pilot project involving human and rodent tissues that are designed to: * Create a database of the genes expressed in insulin-responsive tissues, as well as accessible tissues, that are regulated by insulin, insulin resistance and diabetes. * Assess levels and patterns of gene expression in each tissue before and after insulin stimulation in normal and genetically-modified rodents; normal, insulin resistant and diabetic humans, and in cultured and freshly isolated cell models. * Correlate the level and patterns of expression at the mRNA and/or protein level with the genetic and metabolic phenotype of the animal or cell. * Generate genomic sequence from a panel of humans with type 2 diabetes focusing on the genes most highly regulated by insulin and diabetes to determine the range of sequence and expression variation in these genes and the proteins they encode, which might affect the risk of diabetes or insulin resistance. The DGAP project will define: * the normal anatomy of gene expression, i.e. basal levels of expression and response to insulin. * the morbid anatomy of gene expression, i.e., the impact of diabetes on expression patterns and the insulin response. * the extent to which genetic variability might contribute to the alterations in expression or to diabetes itself.

Proper citation: DGAP (RRID:SCR_003036) Copy   

•   Source: SciCrunch Registry

http://trans.nih.gov/bmap/resources/resources.htm

As part of BMAP gene discovery efforts, mouse brain cDNA libraries and Expressed Sequence Tags (ESTs) have been generated. Through this project a BMAP mouse brain UniGene set consisting of over 24,000 non-redundant members of unique clusters has been developed from EST sequencing of more than 50,000 cDNA clones from 10 regions of adult mouse brain, spinal cord, and retina (http://brainEST.eng.uiowa.edu/). In 2001, NIMH along with NICHD, NIDDK, and NIDA, awarded a contract to the University of Iowa ( M.B. Soares, PI) to isolate full-length cDNA clones corresponding to genes expressed in the developing mouse nervous system and determine their full-coding sequences. The BMAP mouse brain EST sequences can be accessed at NCBI's dbEST database (http://www.ncbi.nlm.nih.gov/dbEST/). Arrayed sets of BMAP mouse brain UniGenes and cDNA libraries, and individual BMAP cDNA clones can be purchased from Open Biosystems, Huntsville, AL (http://www.openbiosystems.com

Proper citation: BMAP cDNA Resources (RRID:SCR_002973) Copy   

•   Source: SciCrunch Registry

http://c3nproject.org/

Project designing, prototyping, optimizing, and evaluating a learning health system to improve clinical practice, patient self-management, and disease outcomes of patients with chronic illness. This open, peer production system combines the collective input of patients, clinicians and researchers. It combines large clinical data registries with patient entered data and makes them accessible and interactive. A platform allows researchers to design, test and implement new knowledge and innovations in patient care. To test their platform approach, C3N is working on a model of treating children with Inflammatory Bowel Disease using the ImproveCareNow Network of pediatric clinics. Following this demonstration phase, the goal is to apply the social, scientific and technical platform to transform the care of a variety of chronic illnesses. The C3N effort has the following goals: # Deploy and optimize an integrated set of engagement tools to make it easier for patients and care providers to collect and use the right information during the clinical encounter and in between visits. # Prototype novel interventions to re-design care delivery by promoting the development of tools for real-time and dynamic population management, "just-in time" scheduling of visits, virtual clinic visits, and measuring the impact of these interventions on health, care, and cost. # Pilot and deploy patient-focused technology to improve the flow of data between patients, clinicians and scientists to enable faster learning and improvement.

Proper citation: Collaborative Chronic Care Network (RRID:SCR_003708) Copy   

•   Source: SciCrunch Registry

http://jdrfconsortium.jaeb.org/

Consortium aiming to accelerate the development of systems for automated control of blood glucose in patients with diabetes. Consortium investigators seek to research and develop strategies, which can be commercialized, that will confer the long-term benefits of improved glycemic control by combining novel automated control algorithms and hormone therapies with continuous glucose monitors and pump devices. The field of closed-loop artificial pancreas research requires expert diabetologists partnering with expert mathematicians and engineers. Consortium investigators include endocrinologists and control theorists at research institutions in the US and in Europe. Many of the diabetes device manufacturers have also participated, providing pumps and sensors with enhanced capabilities that allow for closed-loop experiments to be performed. The goals of the consortium include: * Design, optimization, and clinical testing of multiple algorithmic approaches to closed-loop control * An in silico simulation platform, accepted by the FDA, for validating candidate closed-loop control algorithms in place of animal trials * Reusable templates for constructing the Investigational Device Exemption regulatory documents that must be approved by the FDA prior to any in-clinic, computer-assisted, closed-loop control research involving people * A modular software platform-the Artificial Pancreas System-with a protocol-independent user interface and hooks to incorporate an arbitrary control algorithm and control various continuous glucose monitors and pump devices * A secure consortium Web site with a central repository for experimental data and interfaces to submit candidate control algorithms for centralized validation and to upload or download clinical data sets * the first outpatient studies of an overnight controller * the first outpatient studies of a hypoglycemia minimization strategy * the development and testing of a modular treat-to-range closed-loop approach * multiple studies of dual hormone (insulin and glucagon) devices and a means to improve insulin kinetics Ongoing and recently completed in-clinic studies at the end of 2011 include investigations into hypoglycemia prediction and avoidance as well as fully-automated closed-loop control investigations using MPC and PID/PD-based algorithms. The most recent developments include the first-ever feasibility trials of portable, outpatient-based closed-loop control systems.

Proper citation: JDRF Artificial Pancreas Project Consortium (RRID:SCR_004010) Copy   

•   Source: SciCrunch Registry

http://norccentral.org

Portal to research centers and core facilities specifically support obesity research and better understand the relationship between health and nutrition.

Proper citation: Nutrition and Obesity Research Centers (RRID:SCR_004131) Copy   

•   Source: SciCrunch Registry

https://www.humanislets.com/

Data visualization portal for HumanIslets project. Integrated platform for human islet data access and analysis. Includes data on human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at donor, islet and single-cell levels. Provides set of resources and tools to support metabolism and diabetes research community.

Proper citation: HumanIslets (RRID:SCR_025719) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages/release/bioc/html/HiCDCPlus.html

Software package for Hi-C/HiChIP interaction calling and differential analysis using efficient implementation of HiC-DC statistical framework. Enables principled statistical analysis of Hi-C and HiChIP data sets. Enables systematic 3D interaction calls and differential analysis for Hi-C and HiChIP

Proper citation: HiCDCPlus (RRID:SCR_025317) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/trackViewer.html

Software R package to visualize mapped reads along with annotation as track layers for NGS dataset such as ChIP-seq, RNA-seq, miRNA-seq, DNA-seq, SNPs and methylation data.

Proper citation: trackViewer (RRID:SCR_027743) Copy   

•   Source: SciCrunch Registry

http://cistrome.org

Web based integrative platform for transcriptional regulation studies.

Proper citation: Cistrome (RRID:SCR_000242) Copy   

•   Source: SciCrunch Registry

http://archives.niddk.nih.gov/patient/mpsa/mpsa.aspx

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Cross-disciplinary, multi-institutional network with wide range of experts to analyze serum and tissue samples collected in the Medical Therapy of Prostatic Symptoms (MTOPS) trial. Consortium aims to discover and validate biomarkers for the detection, risk assessment, and disease progression assessment of benign prostatic hyperplasia (BPH).

Proper citation: MTOPS Prostate Samples Analysis Consortium (RRID:SCR_000041) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/X2K/

Software tool to produce inferred networks of transcription factors, proteins, and kinases predicted to regulate the expression of the inputted gene list by combining transcription factor enrichment analysis, protein-protein interaction network expansion, with kinase enrichment analysis. It provides the results as tables and interactive vector graphic figures.

Proper citation: eXpression2Kinases (RRID:SCR_016307) Copy   

•   Source: SciCrunch Registry

https://repository.niddk.nih.gov/study/36

Data set and biosepecimens of a multi-center clinical trial to determine if treatment with beta-cell antigens can delay the onset of Type 1 Diabetes Mellitus (Type 1 DM) in non-diabetic relatives of persons with Type 1 DM. Insulin is a well characterized antigen specifically produced by beta-cells, and it was used for this purpose in the initial DPT-1 studies. The protocol for high risk subjects uses daily subcutaneous insulin injections and an annual course of intravenous insulin treatment, while the protocol for intermediate risk subjects uses daily doses of insulin administered orally. Neither injected nor oral insulin at the doses used were observed to delay or prevent diabetes, although further studies are needed to test whether oral insulin can delay diabetes in people in the intermediate risk group with high titers of insulin autoantibodies.

Proper citation: Diabetes Prevention Type 1 (RRID:SCR_001467) Copy   

•   Source: SciCrunch Registry

https://www.clinicaltrials.gov/study/NCT00360646

Prospective and retrospective registry of well-characterized cases of drug-induced liver disease. The goals of Network include the development of standardized procedures to identify and fully characterize bona fide cases of drug- and complementary and alternative medicines (CAM)-induced liver injury, and to conduct controlled, clinical studies that will include extensive collection of data, serum, DNA, and tissue specimens. Cases of liver injury due to herbal medications are also included. The network will also develop terminology and standardized definitions for DILI, and to develop causality assessment instruments that are sensitive, specific, and reproducible. DILIN is funded by a cooperative agreement and includes five clinical centers and a central data coordinating center. The research goals of DILIN are to: * Create a registry of carefully documented DILI cases * Identify clinical, immunological, and environmental risk factors for drug- and CAM-mediated hepatotoxicity * Create a bank of biological specimens consisting of DNA, plasma, and immortalized lymphocytes to facilitate detailed genetic analyses * Characterize the natural history of drug- and CAM-induced DILI for at least six months following enrollment * Develop the capability to recontact these individuals over an extended period of time so that additional studies exploring DILI mechanisms can be performed Two studies are being initiated by the network. In the Retrospective Study, the implicated drugs are restricted to isoniazid, phenytoin, combination clavulanic acid/amoxicillin, and valproic acid (Depakote), Nitrofurantoin, Trimethoprim-sulfamethoxazole, Minocycline, and Quinolone antibiotics. These drugs were chosen because they are frequently administered to patients not receiving other hepatotoxic drugs, making it easier to establish causality. Patients must be alive, and the date of onset of the DILI episode must be on or after January 1, 1994. In the Prospective Study, all incident cases of drug- and CAM-induced liver injury are being considered. Initial presentation to a healthcare professional must be within the previous six months. A detailed medication history of the implicated DILI drug together with all prescription, OTC, and herbal medications is being recorded. Liver and serological tests are being performed to characterize the injury and to exclude competing causes of liver injury. A blood sample is also being drawn for plasma storage and DNA isolation. These cases will be followed longitudinally to characterize the long-term effects of the DILI episode. For both studies, documented, clinically significant DILI must be recorded in the patient's medical charts so that a causal determination can be made. Patients will be excluded if they are unwilling or unable to provide a blood sample or participate in the genetics component. Children under two years of age at the time of enrollment are excluded due to blood-volume requirements. If you have patients who are eligible to participate in either study, please contact one the DILIN clinical sites. As a general policy, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) invites investigator-initiated research project applications for ancillary studies to ongoing, large-scale clinical trials, epidemiological studies, and disease databases supported by the Institute. These studies are focused on a wide range of diseases and conditions including diabetes, obesity, acute and chronic liver disease, chronic kidney disease, and benign prostatic hyperplasia, among others.

Proper citation: Drug-Induced Liver Injury Network (RRID:SCR_001524) Copy   

•   Source: SciCrunch Registry

https://github.com/hakyimlab/PrediXcan

Software tool to detect known and novel genes associated with disease traits and provide insights into the mechanism of these associations. Used to test the molecular mechanisms through which genetic variation affects phenotype.

Proper citation: PrediXcan (RRID:SCR_016739) Copy   

•   Source: SciCrunch Registry

https://www.sciencescott.com/pyminer

Software tool to automate cell type identification, cell type-specific pathway analyses, graph theory-based analysis of gene regulation, and detection of autocrine-paracrine signaling networks. Finds Gene and Autocrine-Paracrine Networks from Human Islet scRNA-Seq.

Proper citation: PyMINEr (RRID:SCR_016990) Copy   

•   Source: SciCrunch Registry

https://pachterlab.github.io/sleuth/about

Software tool for analysis of RNA-Seq experiments for which transcript abundances have been quantified with kallisto. Used for the differential analysis of gene expression data that utilizes bootstrapping in conjunction with response error linear modeling to decouple biological variance from inferential variance.

Proper citation: sleuth (RRID:SCR_016883) Copy   

•   Source: SciCrunch Registry

https://github.com/kwanjeeraw/metabox

Software R toolbox for thorough metabolomic data analysis, integration and interpretation. Metabox 2.0 is updated version of R package Metabox and includes several methods for data processing, statistical analysis, biomarker analysis, integrative analysis and data interpretation.

Proper citation: Metabox (RRID:SCR_024443) Copy   

•   Source: SciCrunch Registry

http://www.med.unc.edu/cgibd/cores/gnotobiotic

Core facility that supports animal model and basic research projects of CGIBD investigators. Investigators use this resource to examine physiologic and pathophysiologic differences in germ-free, gnotobiotic, and specific pathogen free colonized mice of various genetic backgrounds.

Proper citation: University of North Carolina Center for Gastrointestinal Biology and Disease Gnotobiotic Core (RRID:SCR_015615) Copy   

•   Source: SciCrunch Registry

http://www.med.upenn.edu/genetics/tcmf/

Core facility that provides a centralized service to efficiently produce genetically altered mice for basic research, resulting in reduction in effort and cost to participating investigators.

Proper citation: University of Pennsylvania Center for Molecular Studies in Digestive and Liver Diseases Genetically-Modified Mouse Core (RRID:SCR_015622) Copy   

•   Source: SciCrunch Registry

https://edic.bsc.gwu.edu

Publications from a multi-center, longitudinal, observational study examining the risk factors associated with the long-term complications of type 1 diabetes. The study began in 1994 and follows the 1441 participants previously enrolled in the Diabetes Control and Complications Trial (DCCT), http://diabetes.niddk.nih.gov/dm/pubs/control/index.aspx. The primary aim of EDIC is to examine the long-term effects of conventional vs. intensive diabetes treatment received during the DCCT on the subsequent development and progression of microvascular, neuropathic and cardiovascular complications. This involves studying the influence of genetic factors and other factors such as HbA1c, blood pressure, lipid levels, and treatment modalities on the development and progression of these complications. Annual or biennial measurements (using DCCT methods, standardized protocols and central laboratories) of vascular events, albumin excretion, GFR, ECG, ankle-brachial BP index, serum lipids and HbA1c allows the following analyses: 1) continuation of intention-to-treat analyses to determine long-term effects of prior separation of glycemic levels; 2) risk factors for macrovascular outcomes; 3) correlation of progression of micro- and macrovascular outcomes. The current updated version of the EDIC Protocol is available for download. EDIC is made up of 28 clinical centers, one data coordinating center and one clinical coordinating center.

Proper citation: Epidemiology of Diabetes Interventions and Complications (RRID:SCR_001468) Copy   

•   Source: SciCrunch Registry