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Found 9 result(s)

DrugBank

Open Data Drug & Drug Target Database

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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.

Amsterdam Cohort Studies on HIV infection and AIDS

ACS

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<<<!!!<<< 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.

Genome-Scale Metabolic Network DataBase

GSMNDB

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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

euHCVdb

european Hepatitis C Virus database

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The euHCVdb is mainly oriented towards protein sequence, structure and function analyses and structural biology of HCV.

MetabolomeXchange

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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

LINCS Data Portal

Library of Integrated Network-based Signatures Data Portal

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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.

DEPOD

DEPhOsphorylation Database

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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.

PAIN repository

Pain and Interoception Imaging Network Repository

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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.

The Monarch Initiative

Monarch Initiative

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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.