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Found 37 result(s)
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IID (Integrated Interaction Database) is an on-line database of known and predicted eukaryotic protein-protein interactions, in 30 tissues of model organisms and humans.
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.
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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.
Human Proteinpedia is a community portal for sharing and integration of human protein data. This is a joint project between Pandey at Johns Hopkins University, and Institute of Bioinformatics, Bangalore. This portal allows research laboratories around the world to contribute and maintain protein annotations. Human Protein Reference Database (HPRD) integrates data, that is deposited in Human Proteinpedia along with the existing literature curated information in the context of an individual protein. All the public data contributed to Human Proteinpedia can be queried, viewed and downloaded. Data pertaining to post-translational modifications, protein interactions, tissue expression, expression in cell lines, subcellular localization and enzyme substrate relationships may be deposited.
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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.
>>>!!!<<< as stated 2017-06-09 MPIDB is no longer available under URL http://www.jcvi.org/mpidb/about.php >>>!!!<<< The microbial protein interaction database (MPIDB) aims to collect and provide all known physical microbial interactions. Currently, 24,295 experimentally determined interactions among proteins of 250 bacterial species/strains can be browsed and downloaded. These microbial interactions have been manually curated from the literature or imported from other databases (IntAct, DIP, BIND, MINT) and are linked to 26,578 experimental evidences (PubMed ID, PSI-MI methods). In contrast to these databases, interactions in MPIDB are further supported by 68,346 additional evidences based on interaction conservation, protein complex membership, and 3D domain contacts (iPfam, 3did). We do not include (spoke/matrix) binary interactions infered from pull-down experiments.
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.
Human Protein Reference Database (HPRD) has been established by a team of biologists, bioinformaticists and software engineers. This is a joint project between the PandeyLab at Johns Hopkins University, and Institute of Bioinformatics, Bangalore. HPRD is a definitive repository of human proteins. This database should serve as a ready reckoner for researchers in their quest for drug discovery, identification of disease markers and promote biomedical research in general. Human Proteinpedia (www.humanproteinpedia.org) is its associated data portal.
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!!! Starting September 2013, MINT uses the IntAct database infrastructure to limit the duplication of efforts and to optimise future software development. Data manually curated by the MINT curators can now be accessed from the IntAct homepage at the EBI. Data maintenance and release, MINT PSICQUIC and IMEx services are under the responsibility of the IntAct team, while curation effort will be carried by both groups. The MINT development team now focuses on two new developments: mentha that integrates protein interaction information curated by IMEx databases and SIGNOR a database of logic relationships between human proteins. !!! MINT is a public repository for molecular interactions reported in peer-reviewed journals.IT is a collection of molecular interaction databases that can be used to search for, analyze and graphically display molecular interaction networks and pathways from a wide variety of species. MINT is comprised of separate database components. HomoMINT, is an inferred human protein interatction database. Domino, is database of domain peptide interactions. A new component has been added called VirusMINT that explores the interactions of viral proteins with human proteins.
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Bacteriome.org is a database integrating physical (protein-protein) and functional interactions within the context of an E. coli knowledgebase.
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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).
I2D (Interologous Interaction Database) is an on-line database of known and predicted mammalian and eukaryotic protein-protein interactions. It has been built by mapping high-throughput (HTP) data between species. Thus, until experimentally verified, these interactions should be considered "predictions". It remains one of the most comprehensive sources of known and predicted eukaryotic PPI. I2D includes data for S. cerevisiae, C. elegans, D. melonogaster, R. norvegicus, M. musculus, and H. sapiens.
HPIDB is a public resource, which integrates experimental PPIs from various databases into a single database. The Host-Pathogen Interaction Database (HPIDB) is a genomics resource devoted to understanding molecular interactions between key organisms and the pathogens to which they are susceptible.
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 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.
iRefWeb is an interface to a relational database containing the latest build of the interaction Reference Index (iRefIndex) which integrates protein interaction data from ten different interaction databases: BioGRID, BIND, CORUM, DIP, HPRD, INTACT, MINT, MPPI, MPACT and OPHID.
virus mentha archives evidence about viral interactions 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. virus 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". virus 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. virus mentha offers direct access to viral families such as: Orthomyxoviridae, Orthoretrovirinae and Herpesviridae plus, it offers the unique possibility of searching by host organism. The website and the graphical application are designed to make the data stored in virus mentha accessible and analysable to all users.virus mentha superseeds VirusMINT. The Source databases are: MINT, DIP, IntAct, MatrixDB, BioGRID.
The DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. The data stored within the DIP database were curated, both, manually by expert curators and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Please, check the reference page to find articles describing the DIP database in greater detail. The Database of Ligand-Receptor Partners (DLRP) is a subset of DIP (Database of Interacting Proteins). The DLRP is a database of protein ligand and protein receptor pairs that are known to interact with each other. By interact we mean that the ligand and receptor are members of a ligand-receptor complex and, unless otherwise noted, transduce a signal. In some instances the ligand and/or receptor may form a heterocomplex with other ligands/receptors in order to be functional. We have entered the majority of interactions in DLRP as full DIP entries, with links to references and additional information
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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.
The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans. BioGRID is an online interaction repository with data compiled through comprehensive curation efforts. All interaction data are freely provided through our search index and available via download in a wide variety of standardized formats.
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.
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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.
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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.