The IntAct molecular interaction database in 2010

By Bruno Aranda, P. Achuthan, Y. Alam-Faruque, Irina M. Armean, A. Bridge, C. Derow, Marc Feuermann, A. Ghanbarian, Samuel Kerrien, J. Khadake and 11 more. Nucleic Acids Res., 2009

1,235 citations recorded by the source corpus.

IntAct is an open-source, open data molecular interaction database and toolkit. Data is abstracted from the literature or from direct data depositions by expert curators following a deep annotation model providing a high level of detail. As of September 2009, IntAct contains over 200.000 curated binary interaction evidences. In response to the growing data volume and user requests, IntAct now provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows ‘zooming in’ on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available at http://www.ebi.ac.uk/intact.

Subfields: Computational Theory and Mathematics, Molecular Biology

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Citations in the corpus

Tissue-Specific Functional Networks for Prioritizing Phenotype and Disease Genes (2012, methodology): “…diverse genomic data for mouse as inputs ( Dataset S1 ) to support the functional relationships, including protein-protein physical interactions [21,22,23,24], homologous functional relationship predictions from simpler organisms [9], phenotype and disease data [19,25] and 960 expression datasets,…”
Reactome: a database of reactions, pathways and biological processes (2010, methodology): “PSICQUIC is already widely implemented by interaction databases, including BioGRID, ChEMBL, IntAct, iRefIndex, MINT and STRING (15–20).”
Differential network biology (2012, neutral): “Large network databases such as BioGRID, HPRD, IntAct, DIPand GeneMania (Xenarios et al , 2002; Keshava Prasad et al , 2009; Aranda et al , 2010; Warde-Farley et al , 2010; Stark et al , 2011) record hundreds of thousands of physical and genetic interactions from a wide variety of organisms.”
PATRIC: the Comprehensive Bacterial Bioinformatics Resource with a Focus on Human Pathogenic Species (2011, methodology): ““Experimental Data” (box 2) encompasses transcriptomic data (GEO [6, 7], ArrayExpress [26], and Proteomics Resource Centers [PRCs] [56]), proteomics data from mass spectrometry (Peptidome [25], PRIDE [48] and the PRCs), protein-protein interaction data from the PRCs and IntACt (4), and protein 3-”
The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function (2010, background): “Data sets are collected from publicly available databases, including co-expression data from Gene Expression Omnibus (GEO) (1); physical and genetic interaction data from BioGRID (2); predicted protein interaction data based on orthology from I2D (3); and pathway and molecular interaction data from ”