Filter
Reset all

Subjects

Content Types

Countries

API

Certificates

Data access

Data access restrictions

Database access

Database licenses

Data licenses

Data upload

Enhanced publication

Institution responsibility type

Institution type

Keywords

Metadata standards

PID systems

Provider types

Quality management

Repository languages

Software

Syndications

Repository types

Versioning

  • * at the end of a keyword allows wildcard searches
  • " quotes can be used for searching phrases
  • + represents an AND search (default)
  • | represents an OR search
  • - represents a NOT operation
  • ( and ) implies priority
  • ~N after a word specifies the desired edit distance (fuzziness)
  • ~N after a phrase specifies the desired slop amount
  • 1 (current)
Found 8 result(s)
<<<!!!<<< 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.
Country
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.
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.
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.
Country
<<<!!!<<< 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
ChEMBL is a database of bioactive drug-like small molecules, it contains 2-D structures, calculated properties (e.g. logP, Molecular Weight, Lipinski Parameters, etc.) and abstracted bioactivities (e.g. binding constants, pharmacology and ADMET data). The data is abstracted and curated from the primary scientific literature, and cover a significant fraction of the SAR and discovery of modern drugs We attempt to normalise the bioactivities into a uniform set of end-points and units where possible, and also to tag the links between a molecular target and a published assay with a set of varying confidence levels. Additional data on clinical progress of compounds is being integrated into ChEMBL at the current time.
Country
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.