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https://open.med.harvard.edu/display/SHRINE/Community

Software providing a scalable query and aggregation mechanism that enables federated queries across many independently operated patient databases. This platform enables clinical researchers to solve the problem of identifying sufficient numbers of patients to include in their studies by querying across distributed hospital electronic medical record systems. Through the use of a federated network protocol, SHRINE allows investigators to see limited data about patients meeting their study criteria without compromising patient privacy. This software should greatly enable population-based research, assessment of potential clinical trials cohorts, and hypothesis formation for followup study by combining the EHR assets across the hospital system. In order to obtain the maximum number of cases representing the study population, it is useful to aggregate patient facts across as many sites as possible. Cutting across institutional boundaries necessitates that each hospital IRB remain in control, and that their local authority is recognized for each and every request for patient data. The independence, ownership, and legal responsibilities of hospitals predetermines a decentralized technical approach, such as a federated query over locally controlled databases. The application comes with the SHRINE Core Ontology but it can be used with any ontology, even one that is disease specific. The Core Ontology is designed to enable the widest range of studies possible using facts gathered in the EMR during routine patient care. SHRINE allows multiple ontologies to be used for different research purposes on the same installed systems.

Proper citation: SHRINE (RRID:SCR_006293) Copy   

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http://www.mappd.org/

A database of experimental behavioral data from > 170 aphasia patients who exhibited language impairments secondary to chronic left hemisphere stroke. The core of the database is individual-trial performance data from picture naming. Picture naming is a primary test of lexical processing. The task taps a critical juncture in the language system because naming mediates between high-level conceptual and syntactic processing and low-level phonological processing. Difficulty in this task is present to varying degrees in nearly all aphasic individuals. This site allows researchers to search through naming data from over 170 patients. Searches can narrow in on data subsets based on patient characteristics (e.g. time since aphasia onset, clinical diagnosis), stimulus characteristics (e.g. semantic category, lexical frequency) and task performance (e.g. error type). The data available on this site can be used to test hypotheses about naming impairment and aphasic impairment generally. Once the basic analysis tools of the site are exhausted, users can export the raw data for further analysis and visualization. The web database represents years of data collection. Most were recruited to the research program at Moss Rehabilitation Research Institute (MRRI).

Proper citation: Moss Aphasia Psycholinguistics Project Database (RRID:SCR_006265) Copy   

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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   

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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   

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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   

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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   

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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   

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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   

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http://www.gazel.inserm.fr/

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   

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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   

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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   

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http://www.syapse.com/

A platform and application suite for bringing together omics and clinical data.

Proper citation: Syapse (RRID:SCR_012023) Copy   

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https://biolincc.nhlbi.nih.gov/home/

Repository that serves to coordinate searches across data and biospecimen collections from participants in numerous clinical trials and epidemiologic studies and to provide an electronic means for requests for additional information and the submission of requests for collections. The collections, comprising data from more than 80 trials or studies and millions of biospecimens, are available to qualified investigators under specific terms and conditions consistent with the informed consents provided by the individual study participants. Some datasets are presented with studies and supporting materials to facilitate their use in reuse and teaching. Datasets support basic research, clinical studies, observational studies, and demonstrations. Researchers wishing to apply to submit biospecimen collections to the NHLBI Biorepository for sharing with qualified investigators may also use this website to initiate that process.

Proper citation: Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) (RRID:SCR_013142) Copy   

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https://ckb.jax.org/

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   

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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   

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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   

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http://erin.sfn.org/

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   

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http://cancergenome.nih.gov/

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   

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http://www.mesotissue.org/

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   

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http://www.ebisc.org/

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   

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