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http://nrresource.org

Collection of individual databases on members of the steroid and thyroid hormone receptor superfamily. Although the databases are located on different servers and are managed individually, they each form a node of the NRR. The NRR itself integrates the separate databases and allows an interactive forum for the dissemination of information about the superfamily. NRR Components: Androgen receptor, Estrogen receptor, Glucocorticoid receptor, Peroxisome proliferator, Steroid receptor protein, Thyroid receptor, Vitamin D receptor.

Proper citation: Nuclear Receptor Resource (RRID:SCR_003285) 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

http://www.ndriresource.org/NDRI_Initiatives/HBDI/36/

Database of medical history and genealogical data on over 6700 families who are affected by type 1 diabetes and a repository of DNA and immortalized cell lines collected from 500 families. This database and repository was originally created to help researchers uncover the genetic causes of type 1 diabetes but today, it is also used by researchers who study type 2 diabetes, diabetic complications, autoimmune diseases, kidney disease, and other disorders. The following resources and services are available to researchers through HBDI: * International Type 1 Diabetes Database: This database includes more than 6700 families with diabetes, related complications and other genetic diseases. There are extensive genealogical and medical histories for more than 90,000 individuals. NDRI conducts searches of the database for approved research requests. * HBDI Catalog: The catalog contains 503 family pedigrees with associated cell lines, DNA, and serum for research. Also available are HLA-typing and auto-antibody test results for diabetes families in the catalog. * HBDI Repository: The HBDI repository contains cell lines, DNA, and HLA typing information from 480 families, and frozen buffy coats from 23 families, all with Type 1 diabetes. They have recently expanded the repository to include specimens from individuals with rare diseases. * Customized Collections: NDRI will collect data from patients and physicians, conduct phone interviews and collect blood and other specimens for research on request., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Human Biological Data Interchange (RRID:SCR_004591) Copy   

•   Source: SciCrunch Registry

https://github.com/macs3-project/MACS

Software Python package for identifying transcript factor binding sites. Used to evaluate significance of enriched ChIP regions. Improves spatial resolution of binding sites through combining information of both sequencing tag position and orientation. Can be used for ChIP-Seq data alone, or with control sample with increase of specificity.

Proper citation: MACS (RRID:SCR_013291) Copy   

•   Source: SciCrunch Registry

https://skyline.gs.washington.edu/labkey/project/home/software/Skyline/begin.view

Software tool as Windows client application for targeted proteomics method creation and quantitative data analysis. Open source document editor for creating and analyzing targeted proteomics experiments. Used for large scale quantitative mass spectrometry studies in life sciences.

Proper citation: Skyline (RRID:SCR_014080) Copy   

•   Source: SciCrunch Registry

http://www.cscc.unc.edu/protect/

A study of how children newly diagnosed with ulcerative colitis (UC) respond to mesalamine and prednisone (corticosteroid), the standard initial therapies used to treat this disorder. Over a period of 5 years PROTECT will prospectively study the course of 430 children newly diagnosed with UC who are treated with standardized care. Biospecimens (blood, stool, colonic biopsy tissue) will be obtained and used to better understand the effects of genetics, mechanisms of inflammation, Vitamin D, and the bacteria contained in the stool (microbiome) on clinical outcomes.

Proper citation: Predicting Response to Standardized Pediatric Colitis Therapy (PROTECT) (RRID:SCR_014374) Copy   

•   Source: SciCrunch Registry

http://mmcd.nmrfam.wisc.edu/

A database which supports high-throughput NMR and MS approaches to the identification and quantification of metabolites present in biological samples. MMCD serves as a hub for information on small molecules of biological interest gathered from electronic databases and the scientific literature. Each metabolite entry in the MMCD is supported by information in separate data fields, which provide the chemical formula, names and synonyms, structure, physical and chemical properties, NMR and MS data on pure compounds under defined conditions where available, NMR chemical shifts determined by empirical and/or theoretical approaches, calculated isotopomer masses, information on the presence of the metabolite in different biological species, and links to images, references, and other public databases. The MMCD search engine supports versatile data mining and allows users to make individual or bulk queries on the basis of experimental NMR and/or MS data plus other criteria.

Proper citation: Madison Metabolomics Consortium Database (RRID:SCR_007803) Copy   

•   Source: SciCrunch Registry

https://joslinresearch.org

Diabetes research center which provides patient care and performs diabetes research. Its primary aim is to provide a facilitating framework for conducting multi-disciplinary basic and clinical research and to encourage the scientific development of young investigators.

Proper citation: Joslin Diabetes Center (RRID:SCR_009019) Copy   

•   Source: SciCrunch Registry

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://hembase.niddk.nih.gov/

Database designed for web-based examination of the human erythroid transcriptome. The database is organized to provide a cytogenetic band position, a unique name as well as a concise annotation for each entry. Search queries may be performed by name, keyword or cytogenetic location. Search results are linked to primary sequence data and three major human genome browsers for access to information considered current at the time of each search. Hembase provides interested scientists and clinical hematologists with a genome-based approach toward the study of erythroid biology. Red blood cells in the circulation arise from hematopoietic stem cells that proliferate as erythroid progenitors and differentiate into erythroid precursor cells in response to the hormone erythropoietin. Messenger RNA was isolated from those cells and used to generate gene libraries. Sequencing several thousand expressed sequence tags (EST) from those libraries was then performed. Those EST and sequences encoding several hundred additional genes with known expression in erythroid cells are compiled here as a database of human erythroid gene activity. The database is organized and linked according to the location of these sequences within the human genome., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: HemBase (RRID:SCR_002880) Copy   

•   Source: SciCrunch Registry

http://oligogenome.stanford.edu/

The Stanford Human OligoGenome Project hosts a database of capture oligonucleotides for conducting high-throughput targeted resequencing of the human genome. This set of capture oligonucleotides covers over 92% of the human genome for build 37 / hg19 and over 99% of the coding regions defined by the Consensus Coding Sequence (CCDS). The capture reaction uses a highly multiplexed approach for selectively circularizing and capturing multiple genomic regions using the in-solution method developed in Natsoulis et al, PLoS One 2011. Combined pools of capture oligonucleotides selectively circularize the genomic DNA target, followed by specific PCR amplification of regions of interest using a universal primer pair common to all of the capture oligonucleotides. Unlike multiplexed PCR methods, selective genomic circularization is capable of efficiently amplifying hundreds of genomic regions simultaneously in multiplex without requiring extensive PCR optimization or producing unwanted side reaction products. Benefits of the selective genomic circularization method are the relative robustness of the technique and low costs of synthesizing standard capture oligonucleotide for selecting genomic targets.

Proper citation: OligoGenome (RRID:SCR_006025) Copy   

•   Source: SciCrunch Registry

https://psbweb05.psb.ugent.be/conet/microbialnetworks/spieceasi.php

Software R package estimates inverse covariance matrix from sequencing data.Statistical method for inference of microbial ecological networks from amplicon sequencing datasets.

Proper citation: Sparse Inverse Covariance Estimation for Ecological Association Inference (RRID:SCR_022646) Copy   

•   Source: SciCrunch Registry

https://github.com/compbiolabucf/TEDDY

Software package to impute gene expression for all participants, whether they have partially or completely missing gene expression.

Proper citation: Teddy study IA prediction (RRID:SCR_023303) Copy   

•   Source: SciCrunch Registry

http://www.ndep.nih.gov/

Federal government public education program that promotes diabetes prevention and control. They aim to reduce the morbidity and mortality associated with diabetes and its complications. The NDEP is jointly sponsored by the National Institutes of Health and the Centers for Disease Control and Prevention and over 200 partner organizations. Target audiences include people with diabetes and those at risk, including the racial and ethnic populations disproportionately affected by the disease, health care providers and payers and purchasers of health care.

Proper citation: National Diabetes Education Program (RRID:SCR_001477) Copy   

•   Source: SciCrunch Registry

https://pankbase.org

Centralized knowledge base of the human pancreas for diabetes research. Integrates diverse type 1 diabetes (T1D) datasets with expert-curated knowledge in centralized, open-source data hub. Since users will ultimately be able to contribute their own data, this will be repository for reproducible, collaborative research within the pancreas and T1D realms.

Proper citation: PanKbase (RRID:SCR_026593) 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