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Found 14 result(s)

Human protein-protein interaction network database search

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<<<!!!<<< This repository is no longer available. >>>!!!>>> A human interactome map. The sequencing of the human genome has provided a surprisingly small number of genes, indicating that the complex organization of life is not reflected in the gene number but, rather, in the gene products – that is, in the proteins. These macromolecules regulate the vast majority of cellular processes by their ability to communicate with each other and to assemble into larger functional units. Therefore, the systematic analysis of protein-protein interactions is fundamental for the understanding of protein function, cellular processes and, ultimately, the complexity of life. Moreover, interactome maps are particularly needed to link new proteins to disease pathways and the identification of novel drug targets.

Integrated Interactions Database

IID

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<<<!!!<<< Significantly expanded physical protein interaction database is now available as IID - Integrated Interactions Database. It is 74% larger than I2D and includes annotation of tissue-specific interactions across 30 tissues. https://www.re3data.org/repository/r3d100010675 >>>!!!>>>

Wiki-Pi

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Wiki-Pi is a wiki resource centered on human protein-protein interactions. Wiki-Pi's intuitive search functionality allows you to retrieve and discover interactions effectively.

Bacteriome.org

Bacterial Protein Interaction Database

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Bacteriome.org is a database integrating physical (protein-protein) and functional interactions within the context of an E. coli knowledgebase.

ConsensusPathDB

CPDB

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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.

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.

mentha

the interactome browser

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mentha archives evidence collected from different sources and presents these data in a complete and comprehensive way. Its data comes from manually curated protein-protein interaction databases that have adhered to the IMEx consortium. The aggregated data forms an interactome which includes many organisms. mentha is a resource that offers a series of tools to analyse selected proteins in the context of a network of interactions. Protein interaction databases archive protein-protein interaction (PPI) information from published articles. However, no database alone has sufficient literature coverage to offer a complete resource to investigate "the interactome". mentha's approach generates every week a consistent interactome (graph). Most importantly, the procedure assigns to each interaction a reliability score that takes into account all the supporting evidence. mentha offers eight interactomes (Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Escherichia coli K12, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae) plus a global network that comprises every organism, including those not mentioned. The website and the graphical application are designed to make the data stored in mentha accessible and analysable to all users. Source databases are: MINT, IntAct, DIP, MatrixDB and BioGRID.

APID

Agile Protein Interactomes DataServer

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APID Interactomes is a database that provides a comprehensive collection of protein interactomes for more than 400 organisms based in the integration of known experimentally validated protein-protein physical interactions (PPIs). Construction of the interactomes is done with a methodological approach to report quality levels and coverage over the proteomes for each organism included. In this way, APID provides interactomes from specific organisms that in 25 cases have more than 500 proteins. As a whole APID includes a comprehensive compendium of 90,379 distinct proteins and 678,441 singular interactions. The analytical and integrative effort done in APID unifies PPIs from primary databases of molecular interactions (BIND, BioGRID, DIP, HPRD, IntAct, MINT) and also from experimentally resolved 3D structures (PDB) where more than two distinct proteins have been identified. In this way, 8,388 structures have been analyzed to find specific protein-protein interactions reported with details of their molecular interfaces. APID also includes a new data visualization web-tool that allows the construction of sub-interactomes using query lists of proteins of interest and the visual exploration of the corresponding networks, including an interactive selection of the properties of the interactions (i.e. the reliability of the "edges" in the network) and an interactive mapping of the functional environment of the proteins (i.e. the functional annotations of the "nodes" in the network).

VirHostNet

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VirHostNet is a bioinformatic information system dedidacted to the biocuration, data integration, reproducible systems-level analysis and visualisation of Virus / Host protein-protein interactions Network based on graph theory. VirHostNet is an open and gold standard knowledgebase shared in PSI MITAB 2.5 format using the PSICQUIC webservice and distributed through the NDEx platform. VirHostNet is FAIR and is recognized as a COVID-19 ressource by Elixir bio.tools, the European Virus Bioinformatics Center and FAIRsharing.org.

PSnpBind

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PSnpBind is a large database of protein–ligand complexes covering a wide range of binding pocket mutations and small molecules’ landscape. This database can be used as a source of data for different types of studies, for example, developing machine learning algorithms to predict protein–ligand affinity or mutation's effect on it which requires an extensive amount of data with a wide coverage of mutation types and small molecules. Also, studies of protein-ligand interactions and conformer orientation changes across different mutated versions of a protein can be established using data from PSnpBind.

The Comprehensive Resource of Mammalian protein complexes

CORUM

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CORUM is a manually curated dataset of mammalian protein complexes. Annotation of protein complexes includes protein complex composition and other valuable information such as method of purification, cellular function of complexes or involvement in diseases.

Oral Cancer Gene Database

OrCGDB

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Oral Cancer Gene Database is an initiative of the Advanced Centre for Treatment, Research and Education in Cancer, Navi Mumbai. The present database, version II, consists of 374 genes. It is developed as a user friendly site that would provide the scientist, information and external links from one place. The database is accessed through a list of all genes, and Keyword Search using gene name or gene symbol, chromosomal location, CGH (in %), and molecular weight. Interaction Network shows the interaction between genes for particular biological processes and molecular functions.

HAGR

Human Ageing Genomic Resources

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The Human Ageing Genomic Resources (HAGR) is a collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses.

Comparative Toxicogenomics Database

CTD

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CTD is a robust, publicly available database that aims to advance understanding about how environmental exposures affect human health. It provides manually curated information about chemical–gene/protein interactions, chemical–disease and gene–disease relationships. These data are integrated with functional and pathway data to aid in development of hypotheses about the mechanisms underlying environmentally influenced diseases. We also have additional ongoing projects involving manual curation of exposome data and chemical–phenotype relationships to help identify pre–disease biomarkers resulting from environmental exposures. The initial release of CTD was on November 12, 2004. We’re grateful to our strong community support and encourage you to give us feedback so we can continue to evolve with your research needs.