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Open AccessJournal ArticleDOI

Integration of biological networks and gene expression data using Cytoscape

TLDR
This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest.
Abstract
Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.

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The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible.

TL;DR: In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework.
Journal ArticleDOI

REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms

TL;DR: REVIGO is a Web server that summarizes long, unintelligible lists of GO terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures.
Journal ArticleDOI

Cytoscape 2.8

TL;DR: Version 2.8 introduces two powerful new features—Custom Node Graphics and Attribute Equations—which can be used jointly to greatly enhance Cytoscape's data integration and visualization capabilities.
Journal ArticleDOI

The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored

TL;DR: An update on the online database resource Search Tool for the Retrieval of Interacting Genes (STRING), which provides uniquely comprehensive coverage and ease of access to both experimental as well as predicted interaction information.
References
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Journal ArticleDOI

PhyloFacts: an online structural phylogenomic encyclopedia for protein functional and structural classification

TL;DR: The Berkeley Phylogenomics Group presents PhyloFacts, a structural phylogenomic encyclopedia containing almost 10,000 'books' for protein families and domains, with pre-calculated structural, functional and evolutionary analyses.
Journal ArticleDOI

GenePro: a cytoscape plug-in for advanced visualization and analysis of interaction networks

TL;DR: GenePro, a plugin to Cytoscape featuring a set of versatile tools that greatly facilitates the visualization and analysis of protein networks derived from high-throughput interactions data and the validation of various methods for parsing these networks into meaningful functional modules is presented.
Journal ArticleDOI

The tYNA platform for comparative interactomics

TL;DR: TYNA is a Web system for managing, comparing and mining multiple networks, both directed and undirected, that efficiently implements methods that have proven useful in network analysis, including identifying defective cliques, finding small network motifs and calculating global statistics.
Proceedings ArticleDOI

Estimating and improving protein interaction error rates

TL;DR: A novel method for estimating error rates associated with specific protein interaction data sets, as well as with individual interactions given the data sets in which they appear, and shows how to reach a tradeoff between the "spoke" and "matrix" representation of interactions within co-purified groups of proteins to achieve an optimal false positive error rate.
Journal ArticleDOI

MetaNetwork: a computational protocol for the genetic study of metabolic networks

TL;DR: The MetaNetwork protocol to reconstruct metabolic networks using metabolite abundance data from segregating populations using a two-part model and is able to integrate high-throughput data from subsequent metabolomics, transcriptomics and proteomics experiments in conjunction with traditional phenotypic data.
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