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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 DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information. The latest release of DrugBank (version 5.1.1, released 2018-07-03) contains 11,881 drug entries including 2,526 approved small molecule drugs, 1,184 approved biotech (protein/peptide) drugs, 129 nutraceuticals and over 5,751 experimental drugs. Additionally, 5,132 non-redundant protein (i.e. drug target/enzyme/transporter/carrier) sequences are linked to these drug entries. Each DrugCard entry contains more than 200 data fields with half of the information being devoted to drug/chemical data and the other half devoted to drug target or protein data.
BindingDB is a public, web-accessible knowledgebase of measured binding affinities, focusing chiefly on the interactions of proteins considered to be candidate drug-targets with ligands that are small, drug-like molecules. BindingDB supports medicinal chemistry and drug discovery via literature awareness and development of structure-activity relations (SAR and QSAR); validation of computational chemistry and molecular modeling approaches such as docking, scoring and free energy methods; chemical biology and chemical genomics; and basic studies of the physical chemistry of molecular recognition. BindingDB also includes a small collection of host-guest binding data of interest to chemists studying supramolecular systems. The data collection derives from a variety of measurement techniques, including enzyme inhibition and kinetics, isothermal titration calorimetry, NMR, and radioligand and competition assays. BindingDB includes data extracted from the literature and from US Patents by the BindingDB project, selected PubChem confirmatory BioAssays, and ChEMBL entries for which a well defined protein target ("TARGET_TYPE='PROTEIN'") is provided.
NAHDAP acquires, preserves and disseminates data relevant to drug addiction and HIV research. By preserving and making available an easily accessible library of electronic data on drug addiction and HIV infection in the United States, NAHDAP offers scholars the opportunity to conduct secondary analysis on major issues of social and behavioral sciences and public policy
<<<!!!<<< stated 26-02-2020: Amsterdam Cohort Studies on HIV infection and AIDS is no longer available online >>>!!!>>> The Amsterdam cohort study (ACS) on human immunodeficiency virus (HIV) infection and AIDS among homosexual men started in 1984 and was expanded to include drug users in 1985. Thus far, about 2100 homosexual men and 1630 (injecting) drug users have been included of whom approximately 700 homosexual men and 550 drug users are still in active follow-up. Every 3-6 months participants complete a standardized questionnaire to obtain medical, epidemiological and social scientific information and undergo a medical examination. In addition, they have blood drawn for virological and immunological tests and storage.
The International Union of Basic and Clinical Pharmacology (IUPHAR) / British Pharmacological Society (BPS) Guide to PHARMACOLOGY is an expert-curated resource of ligand-activity-target relationships, the majority of which come from high-quality pharmacological and medicinal chemistry literature. It is intended as a “one-stop shop” portal to pharmacological information and its main aim is to provide a searchable database with quantitative information on drug targets and the prescription medicines and experimental drugs that act on them. In future versions we plan to add resources for education and training in pharmacological principles and techniques along with research guidelines and overviews of key topics. We hope that the IUPHAR/BPS Guide to PHARMACOLOGY (abbreviated as GtoPdb) will be useful for researchers and students in pharmacology and drug discovery and provide the general public with accurate information on the basic science underlying drug action.
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.
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.
Database and knowledgebase of authenticated microbial genomics data with full data provenance to physical materials held within American Type Culture Collection's (ATCC) biorepository and culture collections. Data includes whole genome sequencing data for bacterial, viral and fungal strains at ATCC, their genome assemblies, metadata, drug susceptibility data, and more. All data is freely available for non-commercial research use only (RUO) applications via the web portal interface or via a REST-API. The goal is to provide the research community with provenance information and authentication between the biological source materials and reference genome assemblies derived from them.
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ConsensusPathDB integrates interaction networks in humans (and in the model organisms - yeast and mouse) including binary and complex protein-protein, genetic, metabolic, signaling, gene regulatory and drug-target interactions, as well as biochemical pathways. Data originate from public resources for interactions and interactions curated from the literature. The interaction data are integrated in a complementary manner to avoid redundancies.
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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
Neuroimaging Tools and Resources Collaboratory (NITRC) is currently a free one-stop-shop environment for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, and computing power. Since its debut in 2007, NITRC has helped the neuroscience community to use software and data produced from research that, before NITRC, was routinely lost or disregarded, to make further discoveries. NITRC provides free access to data and enables pay-per-use cloud-based access to unlimited computing power, enabling worldwide scientific collaboration with minimal startup and cost. With NITRC and its components—the Resources Registry (NITRC-R), Image Repository (NITRC-IR), and Computational Environment (NITRC-CE)—a researcher can obtain pilot or proof-of-concept data to validate a hypothesis for a few dollars.
MetabolomeXchange.org delivers the mechanisms needed for disseminating the data to the metabolomics community at large (both metabolomics researchers and databases). The main objective is to make it easier for metabolomics researchers to become aware of newly released, publicly available, metabolomics datasets that may be useful for their research. MetabolomeXchange contains datasets from different data providers: MetaboLights, Metabolomic Repository Bordeaux, Metabolomics Workbench, and Metabolonote
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.
ClinicalTrials.gov is a website and online database of clinical research studies and information about their results. The purpose of ClinicalTrials.gov is to provide information about clinical research studies to the public, researchers, and health care professionals. The U.S. government does not review or approve the safety and science of all studies listed on this website.
The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Data and Specimen Hub (DASH) is a centralized resource that allows researchers to share and access de-identified data from studies funded by NICHD. DASH also serves as a portal for requesting biospecimens from selected DASH studies.
LINCS Data Portal provides access to LINCS data from various sources. The program has six Data and Signature Generation Centers: Drug Toxicity Signature Generation Center, HMS LINCS Center, LINCS Center for Transcriptomics, LINCS Proteomic Characterization Center for Signaling and Epigenetics, MEP LINCS Center, and NeuroLINCS Center.
The central mission of the NACJD is to facilitate and encourage research in the criminal justice field by sharing data resources. Specific goals include providing computer-readable data for the quantitative study of crime and the criminal justice system through the development of a central data archive, supplying technical assistance in the selection of data collections and computer hardware and software for data analysis, and training in quantitative methods of social science research to facilitate secondary analysis of criminal justice data
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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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KiGGS is a long-term study conducted by the Robert Koch Institute (RKI) on the health of children and adolescents in Germany. The study repeatedly supplies data, representative of the country as a whole, on the health of under 18-year-olds. In addition, the children and adolescents of the first KiGGS study are repeatedly invited, and they continue to be monitored right into their adulthood.
DEPOD - the human DEPhOsphorylation Database (version 1.1) is a manually curated database collecting human active phosphatases, their experimentally verified protein and non-protein substrates and dephosphorylation site information, and pathways in which they are involved. It also provides links to popular kinase databases and protein-protein interaction databases for these phosphatases and substrates. DEPOD aims to be a valuable resource for studying human phosphatases and their substrate specificities and molecular mechanisms; phosphatase-targeted drug discovery and development; connecting phosphatases with kinases through their common substrates; completing the human phosphorylation/dephosphorylation network.
The PAIN Repository is a recently funded NIH initiative, which has two components: an archive for already collected imaging data (Archived Repository), and a repository for structural and functional brain images and metadata acquired prospectively using standardized acquisition parameters (Standardized Repository) in healthy control subjects and patients with different types of chronic pain. The PAIN Repository provides the infrastructure for storage of standardized resting state functional, diffusion tensor imaging and structural brain imaging data and associated biological, physiological and behavioral metadata from multiple scanning sites, and provides tools to facilitate analysis of the resulting comprehensive data sets.
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.