Learn to use the IntAct resource, a protein interaction database with valuable tools that can be used to search for, analyze and graphically display protein interaction data from a wide variety of species. IntAct captures protein interaction data from peer-reviewed literature and direct user submissions. The data are generated from a wide variety of techniques and are extremely well-organized into many different levels that are easy to search and understand. This important tool will help the protein interaction researcher find and display interaction data with ease, using a database with over 190,000 binary interactions from over 10,000 curated experiments.
You will learn:
This tutorial is a part of the tutorial group Interaction resources. You might find the other tutorials in the group interesting:
Pathway Interaction Database: A resource of pathway and network data and displays
MINT: Molecular Interaction Database
Cytoscape: An open-source software platform used for visualization and analysis of molecular interaction and network data
BiologicalNetworks: Analyze and visualize molecular interaction networks
BioSystems: Database of Biological Systems
Reactome Legacy: Older version of the current Reactome knowledgebase of biological processes.
Reactome: Knowledgebase of biological processes
GeneMANIA: GeneMANIA: Fast Gene Function Predictions
GenMAPP: A freely available open source software application for visualizing microarray data in the context of biological pathways.
VisANT: A web-based or downloadable software platform used for visualization and analysis of networks and interaction pathways
InterPro: A comprehensive protein signature resource
KEGG: KEGG, The Kyoto Encyclopedia of Genes and Genomes
EBI : This category includes all resources maintained at the European Bioinformatics Institute (EBI)
Proteins : Tools that are primarily used in the storage, retrieval, or exploration of amino acid based data. Some tools may also involve nucleotide sequence information.
Pathways and Interactions : Tools that are involved with protein interactions and pathway features. Some tools are primarily repositories and some offer analysis options.
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Recent BioMed Central research articles citing this resource
Chicco Davide et al., Genome Informatics 2016. Genome Biology (2017) doi:10.1186/s13059-016-1135-5
Serrano-Solano Beatriz et al., How can functional annotations be derived from profiles of phenotypic annotations? Results and data. BMC Bioinformatics (2017) doi:10.1186/s12859-017-1503-5
Taghipour Shirin et al., Improving protein complex prediction by reconstructing a high-confidence protein-protein interaction network of Escherichia coli from different physical interaction data sources. BMC Bioinformatics (2017) doi:10.1186/s12859-016-1422-x
Jamal Salma et al., Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes Proteomics. BMC Genomics (2016) doi:10.1186/s12864-016-3108-1
Wang Xin et al., A network-pathway based module identification for predicting the prognosis of ovarian cancer patients. Journal of Ovarian Research (2016) doi:10.1186/s13048-016-0285-0