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http://ncim.nci.nih.gov/ncimbrowser/
A wide-ranging biomedical terminology database that covers most terminologies used by NCI for clinical care, translational and basic research, and public information and administrative activities. NCIm features: * Maps 4,000,000 terms from more than 75 sources into 2,000,000 biomedical concepts that represent their meaning. * Displays preferred terms, synonyms, definitions, and other information from each source. * Links to NCI Thesaurus and other related information sources. * Contains 22,000,000 cross-links between content elements. * Updated frequently by a team of biomedical terminology and subject matter experts. NCIm contains most public domain terminologies from the National Library of Medicine's UMLS Metathesaurus, as well as many other biomedical terminologies created by or of interest to NCI and its partners. Some propriety terminologies are included, with permission, and have restrictions on their use. The current version of the NCI Metathesaurus, based on the UMLS build 2013AA, covers up to National Cancer Institute Thesaurus, 13.12d. A viewer for the UMLS changes document can be downloaded.
Proper citation: NCI Metathesaurus (RRID:SCR_003565) Copy
http://www.ncbi.nlm.nih.gov/books/NBK1116/
Provides clinically relevant and medically actionable information for inherited conditions in standardized journal-style format, covering diagnosis, management, and genetic counseling for patients and their families. Searchable book of expert-authored, peer-reviewed disease descriptions presented in standardized format and focused on clinically relevant and medically actionable information on diagnosis, management, and genetic counseling of patients and families with specific inherited conditions.
Proper citation: GeneReviews (RRID:SCR_006560) Copy
http://hmut-tr.sourceforge.net/
The Molecular Biology and Genetics Department at Bogazii University is one of the major reference laboratories in Turkey, specialized in molecular analysis of common genetic disorders. Over the years, the rapid accumulation of mutation data in connection with detailed clinical and laboratory information, has led to the idea of establishing a national database for storing, analysing and presenting it in a more efficient and systematic way. For this purpose, an interdisciplinary project was initiated in 1995. b-Thalassemia and Hemophilia-B Databases were selected as preliminary models, for they offer alternative design and implementation strategies due to different clinical and genetic characteristics. b-Thalassemia is an autosomal recessive disorder, characterized by microcytosis and hemolytic anemia, which is the result of reduced b-Globin chain synthesis. In Turkey, the disease is represented with a gene frequency of 2 and reflected by a wide spectrum of clinical manifestations with the presence of more than 40 different mutation. Currently, there is no database available for thalassemia mutations. Hemophilia B is an X-linked recessive disorder caused by heterogenous mutations, resulting in a marked deficit of coagulation factor IX (FIX); an essential component of the clotting mechanism. A hemophilia B database was first published in 1990 as a list of point mutations and short additions and deletions with 115 mutations comprising 216 entries Gene-, System-, or Disease- Specific Databases
Proper citation: Turkish Human Mutation Database (RRID:SCR_008246) Copy
http://bioinfo-out.curie.fr/ittaca/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on 6/12/25. ITTACA is a database created for Integrated Tumor Transcriptome Array and Clinical data Analysis. ITTACA centralizes public datasets containing both gene expression and clinical data and currently focuses on the types of cancer that are of particular interest to the Institut Curie: breast carcinoma, bladder carcinoma, and uveal melanoma. ITTACA is developed by the Institut Curie Bioinformatics group and the Molecular Oncology group of UMR144 CNRS/Institut Curie. A web interface allows users to carry out different class comparison analyses, including comparison of expression distribution profiles, tests for differential expression, patient survival analyses, and users can define their own patient groups according to clinical data or gene expression levels. The different functionalities implemented in ITTACA are: - To test if one or more gene, of your choice, is differentially expressed between two groups of samples exhibiting distinct phenotypes (Student and Wilcoxon tests). - The detection of genes differentially expressed (Significance Analysis of Microarrays) between two groups of samples. - The creation of histograms which represent the expression level according to a clinical parameter for each sample. - The computation of Kaplan Meier survival curves for each group. ITTACA has been developed to be a useful tool for comparing personal results to the existing results in the field of transcriptome studies with microarrays.
Proper citation: Integrated Tumor Transcriptome Array and Clinical data Analysis (RRID:SCR_008182) Copy
http://www.bh4.org/BH4DatabasesBiodef.asp
THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. The BIODEF database have tabulated the most common clinical and laboratory data related to hyperphenylalaninaemia and tetrahydrobiopterin deficiencies. Additionally, there are data regarding treatment, outcome, and DNA analysis. Approximately 2% of newborns with hyperphenylalaninaemia are deficient in tetrahydrobiopterin. Selective screening must be performed in all instances where hyperphenylalaninaemia is detected by neonatal screening. In the last 20 years, 308 patients with tetrahydrobiopterin deficiencies have been recognized as a result of screening carried out, worldwide, in Departments of Paediatrics. Of these 308 patients, 181 suffered from 6-pyruvoyltetrahydropterin synthase deficiency, 92 from dihydropteridine reductase deficiency, 13 from pterin-4a-carbinolamine dehydratase deficiency, 12 from GTP cyclohydrolase I deficiency, and 10 are still unclassified. The BIODEF database have tabulated the most common clinical and laboratory data related to hyperphenylalaninaemia and tetrahydrobiopterin deficiencies. Additionally, there are data regarding treatment, outcome, and DNA analysis. Preliminary evaluation reveals that the degree of hyperphenylalaninaemia can vary from normal to 2500 mumol/L. Analyses of pterins in urine and measurement of dihydropteridine reductase activity from Guthrie cards are absolutely essential tests for accurate diagnosis. There is a regional (demographic) variation in the frequency of tetrahydrobiopterin deficiencies indicating the highest incidence in Saudi Arabia, probably a consequence of the high consanguinity rate.
Proper citation: International Database of Tetrahydrobiopterin Deficiencies (RRID:SCR_008171) Copy
Semi-automated and manually curated database of gene/variant annotations, therapy knowledge, diagnostic/prognostic information, and oncology clinical trials. Users can search CKB via gene, gene variants, drug, drug class, indication, and clinical trials.
Proper citation: Jackson Laboratory Clinical Knowledgebase (RRID:SCR_014965) Copy
http://diabetes.wisc.edu/index.php
Interactive database of gene expression and diabetes related clinical phenotypes. Allows to search gene expression in tissues as a function of obesity, strain, and age, in a mouse.
Proper citation: Attie Lab Diabetes Database (RRID:SCR_016639) Copy
https://www.cdc.gov/nchs/ndi/index.htm
Database of death record information on file in state vital statistics offices. Working with these state offices, the National Center for Health Statistics (NCHS) established the NDI as a resource to aid epidemiologists and other health and medical investigators with their mortality ascertainment activities.
Proper citation: National Death Index (RRID:SCR_016369) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 23,2022. A database that lists, reviews, and rates resources for teaching neuroscience at the graduate and undergraduate level.
Proper citation: Educational Resources in Neuroscience (RRID:SCR_000169) Copy
Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).
Proper citation: The Cancer Genome Atlas (RRID:SCR_003193) Copy
A virtual biospecimen registry designed to support and facilitate basic science, clinical, and translational research that will advance understanding of mesothelioma pathophysiology with the goal of expediting the discovery of preventive measures, novel therapeutic interventions, and ultimately, cures for mesothelioma. The NMVB resource is designed to provide mesothelioma tissue samples with high-quality and well-characterized multimodal annotated data to researchers. The NMVB team strongly believes that progress in translational and clinical research - in cancer as well as other disease areas - depends on the ability of researchers to access high-quality tissue that is associated with meaningful annotation. MVB database version 3.0 has been released that provides researchers real-time access to demographic, epidemiologic, pathologic, genotype, and follow-up data associated with biospecimens at no cost. Researchers interested in utilizing NMVB samples for their research may submit an application. All researchers (academic or commercial, United States or foreign) may apply for NMVB tissue specimens. NMVB currently has 966 annotated cases and 1198 biospecimens including: * Paraffin Embedded Tissue * Fresh Frozen Tissue * Blood and DNA Samples The NMVB also has developed mesothelioma tissue microarrays (TMAs) with associated multimodal data annotation. Additional TMAs will be available shortly.
Proper citation: National Mesothelioma Virtual Bank (RRID:SCR_003438) Copy
Consortium to address the increasing demand by researchers for quality-controlled, disease-relevant research grade induced Pluripotent Stem Cell (iPSC) lines, data and cell services by demonstrating an operational banking and distribution service of iPSC lines after 3 years and establishing subsequently for Europe a centralized, not-for-profit bank providing all qualified users with access to scalable, cost-efficient and customized products. The main facility will be at the Babraham Research Campus (Cambridge, UK) and will undertake cell expansion, QC and characterization. The European Cell Culture Collection (ECACC) of Public Health England (Department of Health, UK) will coordinate cell line distribution. The Fraunhofer IBMT (Saarbr��cken, Germany) will provide comprehensive operational back up. In a phased business strategy EBiSC will hot-start distribution of lines contributed by iPSC Centres in 2014, lines collected based on specified user demand, will reach full scale operations in 2016, and with extended funding will become self-sustaining as a not for profit banking operation by 2019. EBiSC will spearhead Europe in the international standardization of iPSC banking by forging collaborative links with similar endeavors in the USA and Asia. It will also provide training to encourage adoption and use of the bank. The project has up to one year after completion to disseminate intellectual property or data created by the project.
Proper citation: EBiSC (RRID:SCR_003856) Copy
http://www.tmf-ev.de/BiobankenRegisterEN/Registry.aspx?udt_2021_param_detail=72
It is the aim of the SepNet initiative to establish a central facility, essential to data and sample quality and homogeneity, that comprises a structured and easily accessible sample bank with probes of homogeneous quality originating from a well-characterized patient population enrolled in independent, innovative and internationally competitive prospective clinical sepsis trials. The SepNetBiobank is a core facility of SepNet. The object of this central sample resource is to organize and handle all relevant aspects of sampling, storage and delivery of samples in the SepNet collaboration to ensure homogeneity of the samples in terms of specimen quality and maintaining sampling standards. This will be achieved through central handling of samples collected in peripheral nationwide 17 regional centers and an additional 36 associated centers according to an agreed sampling scheme and pre-set standards for sample quality, sample handling and banking; quality assurance and all relevant parts of sample handling will be in the hands of the core unit, minimizing pre-analytical steps in the heterogeneous environment of the different regional centers. In the next few months a fully automated sample storage system will be implemented that allows handling of more than 200.000 individual aliquots expected after completion of the different ongoing and planned SepNet Trails. In the next six months a fully automated -80 degree C sample storage system will be implemented. After completion of the plannend and ongoing SepNet trials more than 59.710 expected primary samples (218.040 aliquots) will be stored in this system. This outstanding sample resource will provide the basis for scientific projects aming at improving patient care with sepsis e.g. advancement in diagnostics, risk stratification, therapy and outcome.
Proper citation: SepNet Central Sample Bank (RRID:SCR_004543) Copy
http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM380961.pdf
An electronically administered patient-reported outcome (PRO) measure that is a qualified measure of symptoms of acute bacterial exacerbation of chronic bronchitis in patients with chronic obstructive pulmonary disease (ABECB-COPD), for use in phase 2 trials. Refer to the proposed context of use, http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/DrugDevelopmentToolsQualificationProgram/UCM399682.pdf. Its intent to quantify frequency, severity, and duration of acute exacerbations in clinical trials of COPD including those with chronic bronchitis. It is designed as an electronic diary made up of fourteen items to be completed by the patient each evening just prior to bedtime. (An item-reduction statistical analysis narrowed the questions from 23 to 14.) For more information see, http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/DrugDevelopmentToolsQualificationProgram/UCM386248.pdf
Proper citation: Exacerbations of Chronic Pulmonary Disease Tool (RRID:SCR_003718) Copy
http://www.uky.edu/coa/adc/investigators-research-resources
An organization which includes a tissue bank, a database, study design consultation, clinical resources, and a community registry database. The UK-ADC shares data with the NIA national database (NACC), as well as with independent, qualified investigators both within and outside the UK-ADC. This resource's associated tissue bank is comprised of anonymized brain tissue, blood, and cerebrospinal fluid samples from patients in the clinic, as well as frozen post-mortem brain tissue samples. This organization also shares research resources with the National Alzheimer's Coordinating Center (NACC), NACC collaborative initiatives, the Alzheimer's Disease Neuroimaging Initiative (ADNI), other Alzheimer Disease Centers (ADCs), and any qualified investigators from either the University of Kentucky or the general scientific community.
Proper citation: University of Kentucky's Alzheimer's Disease Center (RRID:SCR_008766) Copy
http://www.nitrc.org/projects/fluctuations/
The methodology and applications of task independent fluctuation measures including: connectivity maps of fMRI resting state scans, research using EEG/MEG/PET etc, methods to remove non-neural fluctuations, and applications to clinical populations.
Proper citation: Task Independent Fluctuations Discussion (RRID:SCR_009515) Copy
A 20 year, 20,000 person, open longitudinal epidemiological study of a cohort town. GAZEL was not constructed to answer a specific question rather it was designed to help analyze a wide range of scientific problems and is accessible to the community of researchers specializing in epidemiology. Translation is not available for all pages. The GAZEL cohort, set up in 1989 by Inserm Unit 88 (subsequently Unit 687), in cooperation with several departments of ��lectricit�� de France-Gaz de France (EDF-GDF), was a public utility firm in France involved in production, transmission and distribution of energy. GAZEL initially included 20 624 volunteers working at EDF-GDF (15 010 men and 5614 women), aged from 35 to 50 years. In accordance with its purpose as a scientific research platform, the GAZEL cohort is permanently open to epidemiologic research teams. Today, more than 50 projects on very diversified themes have been set up in GAZEL by some 20 teams, French, belonging to different bodies, and foreign (Germany, Belgium, Canada, Great Britain, Sweden, Finland, and USA).
Proper citation: Gazel Database (RRID:SCR_008962) Copy
https://bbgre.brc.iop.kcl.ac.uk
A database and associated tools for investigating the genetic basis of neurodisability. It combines phenotype information from patients with neurodevelopmental and behavioral problems with clinical genetic data, and displays this information on the human genome map. Basic access to genetic information (deletions, duplications) relating to participants with neurodevelopmental disorders is provided without an account; access to the full dataset requires an account. The genetic information that is available to view comprises potentially pathogenic copy number variation across the genome, detected by array comparative genome hybridization (aCGH) using a customized 44K oligonucleotide array.
Proper citation: Brain and Body Genetic Resource Exchange (RRID:SCR_008959) Copy
http://cgap.nci.nih.gov/Chromosomes/Mitelman
The web site includes genomic data for humans and mice, including transcript sequence, gene expression patterns, single-nucleotide polymorphisms, clone resources, and cytogenetic information. Descriptions of the methods and reagents used in deriving the CGAP datasets are also provided. An extensive suite of informatics tools facilitates queries and analysis of the CGAP data by the community. One of the newest features of the CGAP web site is an electronic version of the Mitelman Database of Chromosome Aberrations in Cancer. The data in the Mitelman Database is manually culled from the literature and subsequently organized into three distinct sub-databases, as follows: -The sub-database of cases contains the data that relates chromosomal aberrations to specific tumor characteristics in individual patient cases. It can be searched using either the Cases Quick Searcher or the Cases Full Searcher. -The sub-database of molecular biology and clinical associations contains no data from individual patient cases. Instead, the data is pulled from studies with distinct information about: -Molecular biology associations that relate chromosomal aberrations and tumor histologies to genomic sequence data, typically genes rearranged as a consequence of structural chromosome changes. -Clinical associations that relate chromosomal aberrations and/or gene rearrangements and tumor histologies to clinical variables, such as prognosis, tumor grade, and patient characteristics. It can be searched using the Molecular Biology and Clinical (MBC) Associations Searcher -The reference sub-database contains all the references culled from the literature i.e., the sum of the references from the cases and the molecular biology and clinical associations. It can be searched using the Reference Searcher. CGAP has developed six web search tools to help you analyze the information within the Mitelman Database: -The Cases Quick Searcher allows you to query the individual patient cases using the four major fields: aberration, breakpoint, morphology, and topography. -The Cases Full Searcher permits a more detailed search of the same individual patient cases as above, by including more cytogenetic field choices and adding search fields for patient characteristics and references. -The Molecular Biology Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to gene rearrangements as a consequence of cytogenetic aberrations. -The Clinical Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to clinical associations of cytogenetic aberrations and/or gene rearrangements. -The Recurrent Chromosome Aberrations Searcher provides a way to search for structural and numerical abnormalities that are recurrent, i.e., present in two or more cases with the same morphology and topography. -The Reference Searcher queries only the references themselves, i.e., the references from the individual cases and the molecular biology and clinical associations. Sponsors: This database is sponsored by the University of Lund, Sweden and have support from the Swedish Cancer Society and the Swedish Children''s Cancer Foundation
Proper citation: Mitelman Database of Chromosome Aberrations in Cancer (RRID:SCR_012877) Copy
A platform and application suite for bringing together omics and clinical data.
Proper citation: Syapse (RRID:SCR_012023) Copy
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