Learn to use Cytoscape, an open-source software platform used for visualization and analysis of molecular interaction and network data. Cytoscape uses a graphical user interface with floatable panels to easily manage your network data. Graphical data displays and text attributes provide detailed information about interactions of interest. Customizable features enable extensive visualization and manipulation opportunities. This platform also offers plugin capability to increase functionality, and has an active user community developing and maintaining the software.
Note: This tutorial corresponds to Cytoscape 2.x versions. We are monitoring the releases of the 3.x software and will provide updates in the future.
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
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
IntAct protein interaction database: IntAct is an open source database and analysis resource for protein interaction data
KEGG: KEGG, The Kyoto Encyclopedia of Genes and Genomes
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
Poudel Suresh et al., Integrated omics analyses reveal the details of metabolic adaptation of Clostridium thermocellum to lignocellulose-derived growth inhibitors released during the deconstruction of switchgrass. Biotechnology for Biofuels (2017) doi:10.1186/s13068-016-0697-5
Liu Zhi-Ping et al., Structure alignment-based classification of RNA-binding pockets reveals regional RNA recognition motifs on protein surfaces Structural analysis. BMC Bioinformatics (2017) doi:10.1186/s12859-016-1410-1
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
Chen Qiansi et al., Integrated mRNA and microRNA analysis identifies genes and small miRNA molecules associated with transcriptional and post-transcriptional-level responses to both drought stress and re-watering treatment in tobacco Plant genomics. BMC Genomics (2017) doi:10.1186/s12864-016-3372-0
Tebel Katrin et al., GenomeCAT: a versatile tool for the analysis and integrative visualization of DNA copy number variants Comparative genomics. BMC Bioinformatics (2017) doi:10.1186/s12859-016-1430-x