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Found 55 result(s)
The nationally recognized National Cancer Database (NCDB)—jointly sponsored by the American College of Surgeons and the American Cancer Society—is a clinical oncology database sourced from hospital registry data that are collected in more than 1,500 Commission on Cancer (CoC)-accredited facilities. NCDB data are used to analyze and track patients with malignant neoplastic diseases, their treatments, and outcomes. Data represent more than 70 percent of newly diagnosed cancer cases nationwide and more than 34 million historical records.
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The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research projects from the partner institutions.
The Gene database provides detailed information for known and predicted genes defined by nucleotide sequence or map position. Gene supplies gene-specific connections in the nexus of map, sequence, expression, structure, function, citation, and homology data. Unique identifiers are assigned to genes with defining sequences, genes with known map positions, and genes inferred from phenotypic information. These gene identifiers are used throughout NCBI's databases and tracked through updates of annotation. Gene includes genomes represented by NCBI Reference Sequences (or RefSeqs) and is integrated for indexing and query and retrieval from NCBI's Entrez and E-Utilities systems.
The WorldWide Antimalarial Resistance Network (WWARN) is a collaborative platform generating innovative resources and reliable evidence to inform the malaria community on the factors affecting the efficacy of antimalarial medicines. Access to data is provided through diverse Tools and Resources: WWARN Explorer, Molecular Surveyor K13 Methodology, Molecular Surveyor pfmdr1 & pfcrt, Molecular Surveyor dhfr & dhps.
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Research Data Centres offer a secure access to detailed microdata from Statistics Canada's surveys, and to Canadian censuses' data, as well as to an increasing number of administrative data sets. The search engine was designed to help you find out more easily which dataset among all the surveys available in the RDCs best suits your research needs.
All ADNI data are shared without embargo through the LONI Image and Data Archive (IDA), a secure research data repository. Interested scientists may obtain access to ADNI imaging, clinical, genomic, and biomarker data for the purposes of scientific investigation, teaching, or planning clinical research studies. "The Alzheimer’s Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimer’s disease (AD). ADNI researchers collect, validate and utilize data, including MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors of the disease. Study resources and data from the North American ADNI study are available through this website, including Alzheimer’s disease patients, mild cognitive impairment subjects, and elderly controls. "
Project Data Sphere, LLC, operates a free digital library-laboratory where the research community can broadly share, integrate and analyze historical, de-identified, patient-level data from academic and industry cancer Phase II-III clinical trials. These patient-level datasets are available through the Project Data Sphere platform to researchers affiliated with life science companies, hospitals and institutions, as well as independent researchers, at no cost and without requiring a research proposal.
AceView provides a curated, comprehensive and non-redundant sequence representation of all public mRNA sequences (mRNAs from GenBank or RefSeq, and single pass cDNA sequences from dbEST and Trace). These experimental cDNA sequences are first co-aligned on the genome then clustered into a minimal number of alternative transcript variants and grouped into genes. Using exhaustively and with high quality standards the available cDNA sequences evidences the beauty and complexity of mammals’ transcriptome, and the relative simplicity of the nematode and plant transcriptomes. Genes are classified according to their inferred coding potential; many presumably non-coding genes are discovered. Genes are named by Entrez Gene names when available, else by AceView gene names, stable from release to release. Alternative features (promoters, introns and exons, polyadenylation signals) and coding potential, including motifs, domains, and homologies are annotated in depth; tissues where expression has been observed are listed in order of representation; diseases, phenotypes, pathways, functions, localization or interactions are annotated by mining selected sources, in particular PubMed, GAD and Entrez Gene, and also by performing manual annotation, especially in the worm. In this way, both the anatomy and physiology of the experimentally cDNA supported human, mouse and nematode genes are thoroughly annotated.
The Virtual Research Environment (VRE) is an open-source data management platform that enables medical researchers to store, process and share data in compliance with the European Union (EU) General Data Protection Regulation (GDPR). The VRE addresses the present lack of digital research data infrastructures fulfilling the need for (a) data protection for sensitive data, (b) capability to process complex data such as radiologic imaging, (c) flexibility for creating own processing workflows, (d) access to high performance computing. The platform promotes FAIR data principles and reduces barriers to biomedical research and innovation. The VRE offers a web portal with graphical and command-line interfaces, segregated data zones and organizational measures for lawful data onboarding, isolated computing environments where large teams can collaboratively process sensitive data privately, analytics workbench tools for processing, analyzing, and visualizing large datasets, automated ingestion of hospital data sources, project-specific data warehouses for structured storage and retrieval, graph databases to capture and query ontology-based metadata, provenance tracking, version control, and support for automated data extraction and indexing. The VRE is based on a modular and extendable state-of-the art cloud computing framework, a RESTful API, open developer meetings, hackathons, and comprehensive documentation for users, developers, and administrators. The VRE with its concerted technical and organizational measures can be adopted by other research communities and thus facilitates the development of a co-evolving interoperable platform ecosystem with an active research community.
The National Sleep Research Resource (NSRR) is an NHLBI-supported repository for sharing large amounts of sleep data (polysomnography, actigraphy and questionnaire-based) from multiple cohorts, clinical trials, and other data sources. Launched in April 2014, the mission of the NSRR is to advance sleep and circadian science by supporting secondary data analysis, algorithmic development, and signal processing through the sharing of high-quality data sets.
The Bacterial and Viral Bioinformatics Resource Center (BV-BRC) is an information system designed to support research on bacterial and viral infectious diseases. BV-BRC combines two long-running BRCs: PATRIC, the bacterial system, and IRD/ViPR, the viral systems.
Candida Genome Database, a resource for genomic sequence data and gene and protein information for Candida albicans and related species. CGD is based on the Saccharomyces Genome Database. The Candida Genome Database (CGD) provides online access to genomic sequence data and manually curated functional information about genes and proteins of the human pathogen Candida albicans and related species. C. albicans is the best studied of the human fungal pathogens. It is a common commensal organism of healthy individuals, but can cause debilitating mucosal infections and life-threatening systemic infections, especially in immunocompromised patients. C. albicans also serves as a model organism for the study of other fungal pathogens.
MIDRC aims to develop a high-quality repository for medical images related to COVID-19 and associated clinical data, and develop and foster medical image-based artificial intelligence (AI) for use in the detection, diagnosis, prognosis, and monitoring of COVID-19.
The MG-RAST server is an open source system for annotation and comparative analysis of metagenomes. Users can upload raw sequence data in fasta format; the sequences will be normalized and processed and summaries automatically generated. The server provides several methods to access the different data types, including phylogenetic and metabolic reconstructions, and the ability to compare the metabolism and annotations of one or more metagenomes and genomes. In addition, the server offers a comprehensive search capability. Access to the data is password protected, and all data generated by the automated pipeline is available for download in a variety of common formats. MG-RAST has become an unofficial repository for metagenomic data, providing a means to make your data public so that it is available for download and viewing of the analysis without registration, as well as a static link that you can use in publications. It also requires that you include experimental metadata about your sample when it is made public to increase the usefulness to the community.
TRAILS is a prospective cohort study, which started in 2001 with population cohort and 2004 with a clinical cohort (CC). Since then, a group of 2500 young people from the Northern part of the Netherlands has been closely monitored in order to chart and explain their mental, physical, and social development. These TRAILS participants have been measured every two to three years, by means of questionnaires, interviews, and all kinds of tests. By now, we have collected information that spans the total period from preadolescence up until young adulthood. One of the main goals of TRAILS is to contribute to the knowledge of the development of emotional and behavioral problems and the (social) functioning of preadolescents into adulthood, their determinants, and underlying mechanisms.
The Infectious Diseases Data Observatory (IDDO) assembles clinical, laboratory and epidemiological data on a collaborative platform to be shared with the research and humanitarian communities. The data are analysed to generate reliable evidence and innovative resources that enable research-driven responses to the major challenges of emerging and neglected infections. Access is available to individual patient data held for malaria and Ebola virus disease. Resources for visceral leishmaniasis, schistosomiasis and soil transmitted helminths, Chagas disease and COVID-19 are under development. IDDO contains the following repositories : COVID-19 Data Platform, Chagas Data Platform, Schistosomiasis & Soil Transmitted Helminths Data Platform, Visceral Leishmaniasis Data Platform, Ebola Data Platform, WorldWide Antimalarial Resistance Network (WWARN)
<<<!!!<<< checked 20.03.2017 SumsDB was offline; for more information and archive see http://brainvis.wustl.edu/sumsdb/ >>>!!!>>> SumsDB (the Surface Management System DataBase) is a repository of brain-mapping data (surfaces & volumes; structural & functional data) from many laboratories.
The CONP portal is a web interface for the Canadian Open Neuroscience Platform (CONP) to facilitate open science in the neuroscience community. CONP simplifies global researcher access and sharing of datasets and tools. The portal internalizes the cycle of a typical research project: starting with data acquisition, followed by processing using already existing/published tools, and ultimately publication of the obtained results including a link to the original dataset. From more information on CONP, please visit https://conp.ca
Addgene archives and distributes plasmids for researchers around the globe. They are working with thousands of laboratories to assemble a high-quality library of published plasmids for use in research and discovery. By linking plasmids with articles, scientists can always find data related to the materials they request.
BioLINCC is the Biologic Specimen and Data Repository Coordinating Center. The center coordinates data and biospecimens from NHLBI-funded studies that are available for use in other approved studies. The center also creates teaching data sets from NHLBI-funded studies for use in training future biostatisticians.
The Common Cold Project began in 2011 with the aim of creating, documenting, and archiving a database that combines final research data from 5 prospective viral-challenge studies that were conducted over the preceding 25 years: the British Cold Study (BCS); the three Pittsburgh Cold Studies (PCS1, PCS2, and PCS3); and the Pittsburgh Mind-Body Center Cold Study (PMBC). These unique studies assessed predictor (and hypothesized mediating) variables in healthy adults aged 18 to 55 years, experimentally exposed them to a virus that causes the common cold, and then monitored them for development of infection and signs and symptoms of illness.
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MedEffect Canada’s Adverse Reaction Online Database contains information on suspected adverse reaction reports related to marketed health products that were submitted to Health Canada by consumers and health professionals, who submit reports voluntarily, as well as by Market Authorization Holders (manufacturers and distributors), who are required to submit reports according to the Next link will take you to another Web site Food and Drugs Regulations.