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http://www.autoimmunitycenters.org/

Nine centers that conduct clinical trials and basic research on new immune-based therapies for autoimmune diseases. This program enhances interactions between scientists and clinicians in order to accelerate the translation of research findings into medical applications. By promoting better coordination and communication, and enabling limited resources to be pooled, ACEs is one of NIAID''''s primary vehicles for both expanding our knowledge and improving our ability to effectively prevent and treat autoimmune diseases. This coordinated approach incorporates key recommendations of the NIH Autoimmune Diseases Research Plan and will ensure progress in identifying new and highly effective therapies for autoimmune diseases. ACEs is advancing the search for effective treatments through: * Diverse Autoimmunity Expertise Medical researchers at ACEs include rheumatologists, neurologists, gastroenterologists, and endocrinologists who are among the elite in their respective fields. * Strong Mechanistic Foundation ACEs augment each clinical trial with extensive basic studies designed to enhance understanding of the mechanisms responsible for tolerance initiation, maintenance, or loss, including the role of cytokines, regulatory T cells, and accessory cells, to name a few. * Streamlined Patient Recruitment The cooperative nature of ACEs helps scientists recruit patients from distinct geographical areas. The rigorous clinical and basic science approach of ACEs helps maintain a high level of treatment and analysis, enabling informative comparisons between patient groups.

Proper citation: Autoimmunity Centers of Excellence (RRID:SCR_006510) Copy   

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http://www.ebi.ac.uk/pdbe/emdb/

Repository for electron microscopy density maps of macromolecular complexes and subcellular structures at Protein Data Bank in Europe. Covers techniques, including single-particle analysis, electron tomography, and electron (2D) crystallography.

Proper citation: Electron Microscopy Data Bank at PDBe (MSD-EBI) (RRID:SCR_006506) Copy   

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http://www.nkdep.nih.gov/lab-evaluation/gfr-calculators.shtml

Glomerular Filtration Rate (GFR) calculators to estimate kidney function for adults (MDRD GFR Calculator) and children (Schwartz GFR Calculator). In adults, the recommended equation for estimating glomerular filtration rate (GFR) from serum creatinine is the Modification of Diet in Renal Disease (MDRD) Study equation. The IDMS-traceable version of the MDRD Study equation is used. Currently the best equation for estimating glomerular filtration rate (GFR) from serum creatinine in children is the Bedside Schwartz equation for use with creatinine methods with calibration traceable to IDMS. Using the original Schwartz equation with a creatinine value from a method with calibration traceable to IDMS will overestimate GFR.

Proper citation: Glomerular Filtration Rate Calculators (RRID:SCR_006443) Copy   

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http://www.nkdep.nih.gov/lab-evaluation/gfr/creatinine-standardization.shtml

Standard specification to reduce inter-laboratory variation in creatinine assay calibration and therefore enable more accurate estimates of glomerular filtration rate (eGFR). Created by NKDEP''''s Laboratory Working Group in collaboration with the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) and the European Communities Confederation of Clinical Chemistry (now called the European Federation of Clinical Chemistry and Laboratory Medicine), the effort is part of a larger NKDEP initiative to help health care providers better identify and treat chronic kidney disease in order to prevent or delay kidney failure and improve patient outcomes. Recommendations are intended for the USA and other countries or regions that have largely completed standardization of creatinine calibration to be traceable to an isotope dilution mass spectrometry (IDMS) reference measurement procedure. The program''''s focus is to facilitate the sharing of information to assist in vitro diagnostic manufacturers, clinical laboratories, and others in the laboratory community with calibrating their serum creatinine measurement procedures to be traceable to isotope dilution mass spectrometry (IDMS). The program also supports manufacturers'''' efforts to encourage their customers in the laboratory to coordinate use of standardized creatinine methods with implementation of a revised GFR estimating equation appropriate for use with standardized creatinine methods. Communication resources and other information for various segments of the laboratory community are available in the Creatinine Standardization Recommendations section of the website. Also available is a protocol for calibrating creatinine measurements using whole blood devices. The National Institute for Standards and Technology (NIST) released a standard reference material (SRM 967 Creatinine in Frozen Human Serum) for use in establishing calibrations for routine creatinine measurement procedures. SRM 967 was validated to be commutable with native serum samples for many routine creatinine procedures and is useful to establish or verify traceability to an IDMS reference measurement procedure. Establishing calibrations for serum creatinine methods using SRM 967 not only provides a mechanism for ensuring more accurate measurement of serum creatinine, but also enables more accurate estimates of GFR. For clinical laboratories interested in independently checking the calibration supplied by their creatinine reagent suppliers/manufacturers, periodic measurement of NIST SRM 967 should be considered for inclusion in the lab''''s internal quality assurance program. To learn more about SRM 967, including how to purchase it, visit the NIST website, https://www-s.nist.gov/srmors/quickSearch.cfm

Proper citation: Creatinine Standardization Program (RRID:SCR_006441) Copy   

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http://www.thegpm.org/

The Global Proteome Machine Organization was set up so that scientists involved in proteomics using tandem mass spectrometry could use that data to analyze proteomes. The projects supported by the GPMO have been selected to improve the quality of analysis, make the results portable and to provide a common platform for testing and validating proteomics results. The Global Proteome Machine Database was constructed to utilize the information obtained by GPM servers to aid in the difficult process of validating peptide MS/MS spectra as well as protein coverage patterns. This database has been integrated into GPM server pages, allowing users to quickly compare their experimental results with the best results that have been previously observed by other scientists.

Proper citation: Global Proteome Machine Database (GPM DB) (RRID:SCR_006617) Copy   

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http://www.usrds.org/

Annual report, standard analysis files and an online query system from the national data registry on the end-stage renal disease (ESRD) population in the U.S., including treatments and outcomes. The Annual Data Report is divided into two parts. The Atlas section displays data using graphs and charts. Specific chapters address trends in ESRD patient populations, quality of ESRD care, kidney transplantation outcomes, costs of ESRD care, Healthy People 2010 objectives, chronic kidney disease, pediatric ESRD, and cardiovascular disease special studies. The Reference Tables are devoted entirely to the ESRD population. The RenDER (Renal Data Extraction and Referencing) online data query system allows users to build data tables and maps for the ESRD population. National, state, and county level data are available. USRDS staff collaborates with members of Centers for Medicare & Medicaid Services (CMS), the United Network for Organ Sharing (UNOS), and the ESRD networks, sharing datasets and actively working to improve the accuracy of ESRD patient information.

Proper citation: United States Renal Data System (RRID:SCR_006699) Copy   

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https://www.fludb.org/brc/home.spg?decorator=influenza

The Influenza Research Database (IRD) serves as a public repository and analysis platform for flu sequence, experiment, surveillance and related data.

Proper citation: Influenza Research Database (IRD) (RRID:SCR_006641) Copy   

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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   

•   Source: SciCrunch Registry

http://www.peptideatlas.org

Multi-organism, publicly accessible compendium of peptides identified in a large set of tandem mass spectrometry proteomics experiments. Mass spectrometer output files are collected for human, mouse, yeast, and several other organisms, and searched using the latest search engines and protein sequences. All results of sequence and spectral library searching are subsequently processed through the Trans Proteomic Pipeline to derive a probability of correct identification for all results in a uniform manner to insure a high quality database, along with false discovery rates at the whole atlas level. The raw data, search results, and full builds can be downloaded for other uses. All results of sequence searching are processed through PeptideProphet to derive a probability of correct identification for all results in a uniform manner ensuring a high quality database. All peptides are mapped to Ensembl and can be viewed as custom tracks on the Ensembl genome browser. The long term goal of the project is full annotation of eukaryotic genomes through a thorough validation of expressed proteins. The PeptideAtlas provides a method and a framework to accommodate proteome information coming from high-throughput proteomics technologies. The online database administers experimental data in the public domain. You are encouraged to contribute to the database.

Proper citation: PeptideAtlas (RRID:SCR_006783) Copy   

•   Source: SciCrunch Registry

https://repository.niddk.nih.gov/home/

NIDDK Central Repositories are two separate contract funded components that work together to store data and samples from significant, NIDDK funded studies. First component is Biorepository that gathers, stores, and distributes biological samples from studies. Biorepository works with investigators in new and ongoing studies as realtime storage facility for archival samples.Second component is Data Repository that gathers, stores and distributes incremental or finished datasets from NIDDK funded studies Data Repository helps active data coordinating centers prepare databases and incremental datasets for archiving and for carrying out restricted queries of stored databases. Data Repository serves as Data Coordinating Center and website manager for NIDDK Central Repositories website.

Proper citation: NIDDK Central Repository (RRID:SCR_006542) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/expression.shtml

Community database that collects and integrates the gene expression information in MGI with a primary emphasis on endogenous gene expression during mouse development. The data in GXD are obtained from the literature, from individual laboratories, and from large-scale data providers. All data are annotated and reviewed by GXD curators. GXD stores and integrates different types of expression data (RNA in situ hybridization; Immunohistochemistry; in situ reporter (knock in); RT-PCR; Northern and Western blots; and RNase and Nuclease s1 protection assays) and makes these data freely available in formats appropriate for comprehensive analysis. There is particular emphasis on endogenous gene expression during mouse development. GXD also maintains an index of the literature examining gene expression in the embryonic mouse. It is comprehensive and up-to-date, containing all pertinent journal articles from 1993 to the present and articles from major developmental journals from 1990 to the present. GXD stores primary data from different types of expression assays and by integrating these data, as data accumulate, GXD provides increasingly complete information about the expression profiles of transcripts and proteins in different mouse strains and mutants. GXD describes expression patterns using an extensive, hierarchically-structured dictionary of anatomical terms. In this way, expression results from assays with differing spatial resolution are recorded in a standardized and integrated manner and expression patterns can be queried at different levels of detail. The records are complemented with digitized images of the original expression data. The Anatomical Dictionary for Mouse Development has been developed by our Edinburgh colleagues, as part of the joint Mouse Gene Expression Information Resource project. GXD places the gene expression data in the larger biological context by establishing and maintaining interconnections with many other resources. Integration with MGD enables a combined analysis of genotype, sequence, expression, and phenotype data. Links to PubMed, Online Mendelian Inheritance in Man (OMIM), sequence databases, and databases from other species further enhance the utility of GXD. GXD accepts both published and unpublished data.

Proper citation: Gene Expression Database (RRID:SCR_006539) Copy   

•   Source: SciCrunch Registry

https://www.researchallofus.org

Portal stores health data from participants from across the United States. Provides interactive Data Browser where anyone can learn about the type and quantity of data that All of Us collects. Users can explore aggregate data including genomic variants, survey responses, physical measurements, electronic health record information, and wearables data.

Proper citation: All of Us (RRID:SCR_027032) Copy   

•   Source: SciCrunch Registry

http://teddy.epi.usf.edu/

International consortium of six centers assembled to participate in the development and implementation of studies to identify infectious agents, dietary factors, or other environmental agents, including psychosocial factors, that trigger type 1 diabetes in genetically susceptible people. The coordinating centers recruit and enroll subjects, obtaining informed consent from parents prior to or shortly after birth, genetic and other types of samples from neonates and parents, and prospectively following selected neonates throughout childhood or until development of islet autoimmunity or T1DM. The study tracks child diet, illnesses, allergies and other life experiences. A blood sample is taken from children every 3 months for 4 years. After 4 years, children will be seen every 6 months until the age of 15 years. Children are tested for 3 different autoantibodies. The study will compare the life experiences and blood and stool tests of the children who get autoantibodies and diabetes with some of those children who do not get autoantibodies or diabetes. In this way the study hopes to find the triggers of T1DM in children with higher risk genes.

Proper citation: TEDDY (RRID:SCR_000383) 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   

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http://www.icpsr.umich.edu/icpsrweb/NAHDAP/

Archive that acquires, preserves and disseminates data relevant to drug addiction and HIV research. Collection of data on drug addiction and HIV infection in United States. Most of datasets are raw data from surveys, interviews, and administrative records. They were originally gathered in research projects and for administrative purposes. Some datasets have been used in published studies. Bibliographies of these studies are available . Provides access to research data and technical assistance for data depositors. Provides e-workshops on data preparation and data systems.

Proper citation: National Addiction and HIV Data Archive Program (NAHDAP) (RRID:SCR_000636) Copy   

•   Source: SciCrunch Registry

http://www.genepaint.org/R0_1.htm

A digital atlas of gene expression patterns in the mouse. Expression patterns are determined by non-radioactive in situ hybridization on serial tissue sections. An accompanying atlas based on maps of sagittal sections at embryonic day 14.5. E14.5 NMRI embryo was prepared, sectioned and imaged identically to the embryos used for in situ hybridization. Maps are accessed from the set viewer page using the appropriate button above the image directory. Both, the in situ hybridization section and the appropriate atlas section can be viewed side-by-side. Section thickness is 20 m and inter-section distance is 100 m. Tissue was stained with cresyl violet (Nissl-method). All sections were digitally scanned using a 5x objective. Structures annotated for gene expression are indicated in the maps with red pointers. Boundaries between brain regions are indicated with dashed yellow lines.

Proper citation: GenePaint Interactive Anatomy Atlas (RRID:SCR_007680) Copy   

•   Source: SciCrunch Registry

http://www.ngsp.org

Project that aims to standardize Hemoglobin A1c test results to those of the Diabetes Control and Complications Trial (DCCT) and United Kingdom Prospective Diabetes Study (UKPDS) which established the direct relationships between HbA1c levels and outcome risks in patients with diabetes.

Proper citation: National Glycohemoglobin Standardization Program (RRID:SCR_015885) Copy   

•   Source: SciCrunch Registry

http://dkcoin.org/

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   

•   Source: SciCrunch Registry

https://neuinfo.org/mynif/search.php?list=cover&q=*

Service that partners with the community to expose and simultaneously drill down into individual databases and data sets and return relevant content. This type of content, part of the so called hidden Web, is typically not indexed by existing web search engines. Every record links back to the originating site. In order for NIF to directly query these independently maintained databases and datasets, database providers must register their database or dataset with the NIF Data Federation and specify permissions. Databases are concept mapped for ease of sharing and to allow better understanding of the results. Learn more about registering your resource, http://neuinfo.org/nif_components/disco/interoperation.shtm Search results are displayed under the Data Federation tab and are categorized by data type and nervous system level. In this way, users can easily step through the content of multiple resources, all from the same interface. Each federated resource individually displays their query results with links back to the relevant datasets within the host resource. This allows users to take advantage of additional views on the data and tools that are available through the host database. The NIF site provides tutorials for each resource, indicated by the Professor Icon professor icon showing users how to navigate the results page once directed there through the NIF. Additionally, query results may be exported as an Excel document. Note: NIF is not responsible for the availability or content of these external sites, nor does NIF endorse, warrant or guarantee the products, services or information described or offered at these external sites. Integrated Databases: Theses virtual databases created by NIF and other partners combine related data indexed from multiple databases and combine them into one view for easier browsing. * Integrated Animal View * Integrated Brain Gene Expression View * Integrated Disease View * Integrated Nervous System Connectivity View * Integrated Podcasts View * Integrated Software View * Integrated Video View * Integrated Jobs * Integrated Blogs For a listing of the Federated Databases see, http://neuinfo.org/mynif/databaseList.php or refer to the Resources Listed by NIF Data Federation table below.

Proper citation: NIF Data Federation (RRID:SCR_004834) 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