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A database which provides ribosome related data services to the scientific community, including online data analysis, rRNA derived phylogenetic trees, and aligned and annotated rRNA sequences. It specifically contains information on quality-controlled, aligned and annotated bacterial and archaean 16S rRNA sequences, fungal 28S rRNA sequences, and a suite of analysis tools for the scientific community. Most of the RDP tools are now available as open source packages for users to incorporate in their local workflow.
Proper citation: Ribosomal Database Project (RRID:SCR_006633) Copy
http://diabetes.niddk.nih.gov/dm/pubs/america/
A compilation and assessment of epidemiologic, public health, and clinical data on diabetes and its complications in the United States. Published by the National Diabetes Data Group of the National Institute of Diabetes and Digestive and Kidney Diseases, the book contains 36 chapters organized in five areas: * the descriptive epidemiology of diabetes in the United States based on national surveys and community-based studies, including prevalence, incidence, sociodemographic and metabolic characteristics, risk factors for developing diabetes, and mortality * the myriad complications that affect patients with diabetes * characteristics of therapy and medical care for diabetes * economic aspects, including health insurance and health care costs * diabetes in special populations, including African Americans, Hispanics, Asian and Pacific Islanders, Native Americans, and pregnant women. Diabetes in America, 2nd Edition, has been designed to serve as a reliable scientific resource for assessing the scope and impact of diabetes and its complications, determining health policy and priorities in diabetes, and identifying areas of need in research. The intended audience includes health policy makers at the local and Federal levels who need a sound quantitative base of knowledge to use in decision making; clinicians who need to know the probability that their patients will develop diabetes and the prognosis of the disease for complications and premature mortality; persons with diabetes and their families who need sound information on which to make decisions about their life with diabetes; and the research community which needs to identify areas where important scientific knowledge is lacking.
Proper citation: Diabetes in America (RRID:SCR_006754) Copy
http://ligand-expo.rutgers.edu/
An integrated data resource for finding chemical and structural information about small molecules bound to proteins and nucleic acids within the structure entries of the Protein Data Bank. Tools are provided to search the PDB dictionary for chemical components, to identify structure entries containing particular small molecules, and to download the 3D structures of the small molecule components in the PDB entry. A sketch tool is also provided for building new chemical definitions from reported PDB chemical components.
Proper citation: Ligand Expo (RRID:SCR_006636) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented October 13, 2014. The resource has moved to the NIDDKInformation Network (dkNET) project. Contact them at info_at_dknet.org with any questions. Database of large pools of data relevant to the mission of NIDDKwith the goal of developing a community-based network for integration across disciplines to include the larger DKuniverse of diseases, investigators, and potential users. The focus is on greater use of this data with the objective of adding value by breaking down barriers between sites to facilitate linking of different datasets. To date (2013/06/10), a total of 1,195 resources have been associated with one or more genes. Of 11,580 total genes associated with resources, the ten most represented are associated with 359 distinct resources. The main method by which they currently interconnect resources between the providers is via EntrezGene identifiers. A total of 780 unique genes provide the connectivity between 3,159 resource pairs across consortia. To further increase interconnectivity, the groups have been further annotating their data with additional gene identifiers, publications, and ontology terms from selected Open Biological and Biomedical Ontologies (OBO).
Proper citation: dkCOIN (RRID:SCR_004438) Copy
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
Software tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.
Proper citation: HOMER (RRID:SCR_010881) Copy
http://bioplex.hms.harvard.edu/
Database of cell lines with each expressing a tagged version of a protein from the ORFeome collection. The overarching project goal is to determine protein interactions for every member of the collection.
Proper citation: BioPlex (RRID:SCR_016144) 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://hirnetwork.org/consortium/ctar
Consortium that is an independent research initiative of the Human Research Information Network (HIRN). It is investigating methods to increase or maintain functional beta cell mass in T1D through targeted manipulation of islet plasticity or engineered protection of beta cells from immune-mediated destruction.
Proper citation: HIRN Consortium on Targeting and Regeneration (RRID:SCR_016201) Copy
https://hirnetwork.org/consortium/chib
Consortium that is an independent research initiative of the Human Research Information Network (HIRN). It is combining advances in beta cell biology and cell biology with tissue engineering technologies to develop microdevices that support functional human islets.
Proper citation: HIRN Consortium on Human Islet Biomimetics (RRID:SCR_016199) Copy
https://hirnetwork.org/consortium/cbds
Consortium that is an independent research initiative of the Human Research Information Network (HIRN). It is using human tissues to discover highly specific biomarkers of beta cell injury in asymptomatic T1D and developing strategies to stop beta cell destruction early in the disease process.
Proper citation: HIRN Consortium on Beta Cell Death and Survival (RRID:SCR_016198) 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
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
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
Center mission is to advance medical and biological research by providing the scientific community with standardized, high quality metabolic and physiologic phenotyping services for mouse models of diabetes, diabetic complications, obesity and related disorders.
Proper citation: National Mouse Metabolic Phenotyping Centers (RRID:SCR_008997) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 5, 2022. Endoscopic Reporting Software, aggregated and individual research data and tailor-made services aimed to advance the overall practice of endoscopy. It was developed to study outcomes of gastrointestinal (GI) endoscopic procedures in real life settings, using data obtained from the CORI Endoscopic Reporting Software or from other endoscopic reporting software. Practice sites include hospitals, ambulatory care centers, private practices, universities, and Veteran''''s hospitals (VA''''s). The CORI v4 Endoscopic Reporting Software is a specialty Electronic Health Record used to document endoscopic procedures and provide reporting services to your practice. Data from participating providers is also sent to a central data repository to become part of the National Endoscopic Database (NED), which now contains data from over 2.7 million GI procedures. The CORI v4 Endoscopic Reporting Software offers significant benefits for participating practices, providers and patients, as well as for everyone who benefits from CORI''''s research efforts. You may actively participate in research with CORI. If you have ideas for research using the NED, their research team can help you evaluate those ideas, collect and analyze the data. In addition, you may choose to participate in one of the prospective research projects conducted by CORI research staff.
Proper citation: Clinical Outcomes Research Initiative (RRID:SCR_009010) Copy
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