Filter
Reset all

Subjects

Content Types

Countries

AID systems

API

Data access

Data access restrictions

Database access

Database access restrictions

Database licenses

Data licenses

Data upload

Data upload restrictions

Enhanced publication

Institution responsibility type

Institution type

Keywords

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 5 result(s)
BindingDB is a public, web-accessible database 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 by the BindingDB project, selected PubChem confirmatory BioAssays, and ChEMBL entries for which a well defined protein target ("TARGET_TYPE='PROTEIN'") is provided. Data extracted by BindingDB typically includes more details regarding experimental conditions, etc
Content type(s)
Country
The GISAID Initiative promotes the international sharing of all influenza virus sequences, related clinical and epidemiological data associated with human viruses, and geographical as well as species-specific data associated with avian and other animal viruses, to help researchers understand how the viruses evolve, spread and potentially become pandemics. *** GISAID does so by overcoming disincentives/hurdles or restrictions, which discourage or prevented sharing of influenza data prior to formal publication. *** The Initiative ensures that open access to data in GISAID is provided free-of-charge and to everyone, provided individuals identify themselves and agree to uphold the GISAID sharing mechanism governed through its Database Access Agreement. GISAID calls on all users to agree to the basic premise of upholding scientific etiquette, by acknowledging the originating laboratories providing the specimen and the submitting laboratories who generate the sequence data, ensuring fair exploitation of results derived from the data, and that all users agree that no restrictions shall be attached to data submitted to GISAID, to promote collaboration among researchers on the basis of open sharing of data and respect for all rights and interests.
The Cancer Cell Line Encyclopedia project is a collaboration between the Broad Institute, and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models, to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.
The Open PHACTS project will develop an open source, open standards and open access innovation platform, Open Pharmacological Space (OPS), via a semantic web approach. OPS will comprise data, vocabularies and infrastructure needed to accelerate drugoriented research. This semantic integration hub will address key bottlenecks in small molecule drug discovery: disparate information sources, lack of standards and shared concept identifiers, guided by well defined research questions assembled from participating drug discovery teams. Open PHACTS draws together multiple sources of publicly-available pharmacological and physicochemical data, accessible via the Open PHACTS Explorer, an intuitive interface, and the powerful Open PHACTS API.