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Found 25 result(s)
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SIDER contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. The available information include side effect frequency, drug and side effect classifications as well as links to further information, for example drug–target relations.
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The COVID-19 pandemic has affected every country in the world. It is well documented that those most susceptible to the worst outcomes of COVID-19 are the immunocompromised and those with underlying comorbidities. Therefore, patients requiring treatment for COVID-19 will also be on additional medication, posing a risk for drug-drug interactions (DDIs). In order to address this, the Liverpool Drug Interactions website team developed this freely available drug interactions resource to provide information on the likelihood of interactions between the experimental agents used for the treatment of COVID-19 and commonly prescribed co-medications.
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Since 2004, the Leibniz Institute for Prevention Research and Epidemiology – BIPS has been working on the establishment and maintenance of the project-based German Pharmacoepidemiological Research Database (short GePaRD). GePaRD is based on claims data from statutory health insurance (SHI) providers and currently includes information on about 20 million persons who have been insured with one of the participating providers since 2004. Per data year, there is information on approximately 17% of the general population from all geographical regions of Germany.
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The database aims to bridge the gap between agent repositories and studies documenting the effect of antimicrobial combination therapies. Most notably, our primary aim is to compile data on the combination of antimicrobial agents, namely natural products such as AMP. To meet this purpose, we have developed a data curation workflow that combines text mining, manual expert curation and graph analysis and supports the reconstruction of AMP-Drug combinations.
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<<<!!!<<< This repository is no longer available. >>>!!!>>>
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Patients-derived tumor xenograft (PDX) mouse models are an important oncology research platform to study tumor evolution, drug response and personalised medicine approaches.
We have expanded to organoids and cell lines and are now called CancerModels.Org
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This site is dedicated to making high value health data more accessible to entrepreneurs, researchers, and policy makers in the hopes of better health outcomes for all. In a recent article, Todd Park, United States Chief Technology Officer, captured the essence of what the Health Data Initiative is all about and why our efforts here are so important.
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The Coronavirus Antiviral Research Database is designed to expedite the development of SARS-CoV-2 antiviral therapy. It will benefit global coronavirus drug development efforts by (1) promoting uniform reporting of experimental results to facilitate comparisons between different candidate antiviral compounds; (2) identifying gaps in coronavirus antiviral drug development research; (3) helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development; (4) providing an objective, evidenced-based, source of information for the public; and (5) creating a hub for the exchange of ideas among coronavirus researchers whose feedback is sought and welcomed. By comprehensively reviewing all published laboratory, animal model, and clinical data on potential coronavirus therapies, the Database makes it unlikely that promising treatment approaches will be overlooked. In addition, by making it possible to compare the underlying data associated with competing treatment strategies, stakeholders will be better positioned to prioritize the most promising anti-coronavirus compounds for further development.
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An interactive database hosted by Collaborative Drug Discovery for antibiotic susceptibility data (MIC and IC50). Data is extracted from journal articles and/or contributed by different organizations and individuals. In some cases, the data has not previously been published. Access to the database is open to everyone and can be requested at pewtrusts.org/spark-antibiotic-discovery.
Effective November 18, 2021, Pew transferred all SPARK data to The University of Queensland’s Community for Open Antimicrobial Drug Discovery (CO-ADD). Please visit spark.co-add.org https://co-add.org/.
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The goal of the Autophagy Database is to provide up-to-date relevant information including protein structure data to researchers of autophagy, and to disseminate important findings to a wider audience so that their ramifications can be appreciated. For this purpose, we strive to make the database to contain as much pertinent information as possible and to make the contents freely available in a user-friendly format.
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Wiki-Pi is a wiki resource centered on human protein-protein interactions. Wiki-Pi's intuitive search functionality allows you to retrieve and discover interactions effectively.
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- Basic Biological and Medical Research
- Medical Microbiology, Molecular Infection Biology
- Epidemiology, Medical Biometry, Medical Informatics
- Pneumology, Clinical Infectiology Intensive Care Medicine
- Biomedical Technology and Medical Physics
- Biology
- Life Sciences
- Microbiology, Virology and Immunology
- Medicine
- Medicine
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<<<!!!<<< As detected 2017-11-24 TBNet India is no longer accessible >>>!!!>>> TBNet India is an initiative by the Department of Biotechnology, Govt of India with special focus on Indian contributions on research and various issues related to tuberculosis. Around 13 institutions across India are apart of this initiative. TB Net India focuses to gather clinical, epidemiological and molecular data and make it available to the biomedical community.
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Bioinformatics.org serves the scientific and educational needs of bioinformatic practitioners and the general public. We develop and maintain computational resources to facilitate world-wide communications and collaborations between people of all educational and professional levels. We provide and promote open access to the materials and methods required for, and derived from, research, development and education.
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ProteomicsDB started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and cell line viability data.
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<<<!!!<<< 2019-12-23: the repository is offline >>>!!!>>> Introduction of genome-scale metabolic network:
The completion of genome sequencing and subsequent functional annotation for a great number of species enables the reconstruction of genome-scale metabolic networks. These networks, together with in silico network analysis methods such as the constraint based methods (CBM) and graph theory methods, can provide us systems level understanding of cellular metabolism. Further more, they can be applied to many predictions of real biological application such as: gene essentiality analysis, drug target discovery and metabolic engineering
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The euHCVdb is mainly oriented towards protein sequence, structure and function analyses and structural biology of HCV.
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<<<!!!<<< This repository is no longer available. >>>!!!>>> A human interactome map. The sequencing of the human genome has provided a surprisingly small number of genes, indicating that the complex organization of life is not reflected in the gene number but, rather, in the gene products – that is, in the proteins. These macromolecules regulate the vast majority of cellular processes by their ability to communicate with each other and to assemble into larger functional units. Therefore, the systematic analysis of protein-protein interactions is fundamental for the understanding of protein function, cellular processes and, ultimately, the complexity of life. Moreover, interactome maps are particularly needed to link new proteins to disease pathways and the identification of novel drug targets.
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The ABCD Data Repository houses all data generated by the Adolescent Brain Cognitive Development (ABCD) Study. The ABCD Study is supported by NIH partners (the National Institute on Drug Abuse, the National Institute on Alcohol Abuse and Alcoholism, the National Cancer Institute, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Institute of Mental Health, the National Institute on Minority Health and Health Disparities, the National Institute of Neurological Disorders and Stroke, the NIH Office of Behavioral and Social Sciences Research, and the NIH Office of Research on Women’s Health), as well as the Centers for Disease Control and Prevention – Division of Adolescent and School Health. This repository will store data generated by ABCD investigators, serve as a collaborative platform for harmonizing these data, and share those data with qualified researchers.
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Human Protein Reference Database (HPRD) has been established by a team of biologists, bioinformaticists and software engineers. This is a joint project between the PandeyLab at Johns Hopkins University, and Institute of Bioinformatics, Bangalore. HPRD is a definitive repository of human proteins. This database should serve as a ready reckoner for researchers in their quest for drug discovery, identification of disease markers and promote biomedical research in general.
Human Proteinpedia (www.humanproteinpedia.org) is its associated data portal.
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The National Human Disease Animal Model Resource Bank is supported by the Institute of Medical Laboratory Animals, Chinese Academy of Medical Sciences. The institute is a professional institute engaged in the scientific research and teaching of experimental zoology and comparative medicine. The research unit is the undertaking unit of the national-level laboratory animal technology resource bank for infectious diseases and new drug creation research. In 2015, it established the Key Laboratory of Animal Model Research for Infectious Diseases, the Beijing Engineering Technology Research Center for Laboratory Animal Models of Human Diseases, and established the Human Disease Animal Model Resource Center of the Chinese Academy of Medical Sciences in 2015. The institute has passed CNAS measurement certification, national laboratory accreditation and international AAALAC certification.
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This repository accepts data from life science researchers and service units in Sweden. The repository is operated by SciLifeLab, which is the national infrastructure for life science and environmental research in Sweden. This repository replaces NBIS DOI repository: https://doi.org/10.17616/R3CW52
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>>>!!!<<< The NCI Cancer Models Database, caMOD, was retired on December 24, 2015. Information about many of the mouse models hosted in caMOD was obtained from the Jackson Laboratory Mouse Tumor Biology (MTB) Database and can be accessed through that resource http://tumor.informatics.jax.org/mtbwi/index.do . See caMOD Retirement Announcement https://wiki.nci.nih.gov/display/caMOD/caMOD+Retirement+Announcement >>>>!!<<< Query the Cancer Models database for models submitted by fellow researchers. Retrieve information about the making of models, their genetic description, histopathology, derived cell lines, associated images, carcinogenic agents, and therapeutic trials. Links to associated publications and other resources are provided.
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The Small Molecule Pathway Database (SMPDB) contains small molecule pathways found in humans, which are presented visually. All SMPDB pathways include information on the relevant organs, subcellular compartments, protein cofactors, protein locations, metabolite locations, chemical structures and protein quaternary structures. Accompanying data includes detailed descriptions and references, providing an overview of the pathway, condition or processes depicted in each diagram.
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The OpenNeuro project (formerly known as the OpenfMRI project) was established in 2010 to provide a resource for researchers interested in making their neuroimaging data openly available to the research community. It is managed by Russ Poldrack and Chris Gorgolewski of the Center for Reproducible Neuroscience at Stanford University. The project has been developed with funding from the National Science Foundation, National Institute of Drug Abuse, and the Laura and John Arnold Foundation.
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As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest. We import data from a variety of data sources. With many resources integrated into a single database, we can join across the various data sources to produce integrated views. We have started with the big players including ClinVar and OMIM, but are equally interested in boutique databases. You can learn more about the sources of data that populate our system from our data sources page https://monarchinitiative.org/about/sources.
- Current projects
- EOSC FAIR-IMPACT
- re3data COREF
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- Cite this service: re3data.org - Registry of Research Data Repositories. https://doi.org/10.17616/R3D last accessed: 2024-05-11
