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Found 9 result(s)

STRING

Known and Predicted Protein-Protein Interactions

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STRING is a database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations; they are derived from four sources: - Genomic Context - High-throughput Experiments - (Conserved) Coexpression - Previous Knowledge STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable.

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

Edinburgh DataShare

DataShare

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Edinburgh DataShare is a digital repository of research data produced at the University of Edinburgh, hosted by the Research Data Service in Information Services. Edinburgh University researchers who have produced research data associated with an existing or forthcoming publication, or which has potential use for other researchers, are invited to upload their dataset for sharing and safekeeping. A persistent identifier and suggested citation will be provided.

The Human Protein Atlas

HPA

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The Swedish Human Protein Atlas project has been set up to allow for a systematic exploration of the human proteome using Antibody-Based Proteomics. This is accomplished by combining high-throughput generation of affinity-purified antibodies with protein profiling in a multitude of tissues and cells assembled in tissue microarrays. Confocal microscopy analysis using human cell lines is performed for more detailed protein localization. The program hosts the Human Protein Atlas portal with expression profiles of human proteins in tissues and cells. The main objective of the resource centre is to produce specific antibodies to human target proteins using a high-throughput production method involving the cloning and protein expression of Protein Epitope Signature Tags (PrESTs). After purification, the antibodies are used to study expression profiles in cells and tissues and for functional analysis of the corresponding proteins in a wide range of platforms.

PDBj

Protein Data Bank Japan

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PDBj (Protein Data Bank Japan) provides a centralized PDB archive of macromolecular structures, integrated tools for data retrieval, visualization, and functional characterization. PDBj is supported by JST-NBDC and Osaka University.

STITCH 4.0

Search Tool for Interactions of Chemicals

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The Database explores the interactions of chemicals and proteins. It integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins.

BioImage Archive

BIA

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The BioImage Archive stores and distributes life sciences imaging datasets. It supports deposition of biological imaging data associated with publications for the whole research community, as well as reference imaging datasets. All data deposited to the BioImage Archive is made openly accessible to the scientific community.

Top Down Proteomics Repository

TDPR

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This database will provide a central location for scientists to browse uniquely observed proteoforms and to contribute their own datasets. Top-down proteomics is a method of protein identification that uses an ion trapping mass spectrometer to store an isolated protein ion for mass measurement and tandem mass spectrometry analysis.

SwissLipids

Swiss+Lipids

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SwissLipids is an expert curated resource that provides a framework for the integration of lipid and lipidomic data with biological knowledge and models.