ArticleBMC systems biology2008
Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle.
Article in BMC systems biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- MUFINS: multi-formalism interaction network simulator.NPJ systems biology and applications · 2016Article
- Systems biology approaches for studying the pathogenesis of non-alcoholic fatty liver disease.World journal of gastroenterology · 2014Review
- QSSPN: dynamic simulation of molecular interaction networks describing gene regulation, signalling and whole-cell metabolism in human cells.Bioinformatics (Oxford, England) · 2013Article
- Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.Pharmacology & therapeutics · 2013Review
- Modeling integrated cellular machinery using hybrid Petri-Boolean networks.PLoS computational biology · 2013Article
- Article
- Learning cellular sorting pathways using protein interactions and sequence motifs.Journal of computational biology : a journal of computational molecular cell biology · 2011Article
- Odefy--from discrete to continuous models.BMC bioinformatics · 2010Article
- Nuclear ribosomal spacer regions in plant phylogenetics: problems and prospects.Molecular biology reports · 2010Article
- FORG3D: force-directed 3D graph editor for visualization of integrated genome scale data.BMC systems biology · 2009Article
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3 authors.
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Abstract
backgroundIn systems biology the experimentalist is presented with a selection of software for analyzing dynamic properties of signaling networks. These tools either assume that the network is in steady-state or require highly parameterized models of the network of interest. For biologists interested in assessing how signal propagates through a network under specific conditions, the first class of methods does not provide sufficiently detailed results and the second class requires models which may not be easily and accurately constructed. A tool that is able to characterize the dynamics of a signaling network using an unparameterized model of the network would allow biologists to quickly obtain insights into a signaling network's behavior.
resultsWe introduce PathwayOracle, an integrated suite of software tools for computationally inferring and analyzing structural and dynamic properties of a signaling network. The feature which differentiates PathwayOracle from other tools is a method that can predict the response of a signaling network to various experimental conditions and stimuli using only the connectivity of the signaling network. Thus signaling models are relatively easy to build. The method allows for tracking signal flow in a network and comparison of signal flows under different experimental conditions. In addition, PathwayOracle includes tools for the enumeration and visualization of coherent and incoherent signaling paths between proteins, and for experimental analysis - loading and superimposing experimental data, such as microarray intensities, on the network model.
conclusionPathwayOracle provides an integrated environment in which both structural and dynamic analysis of a signaling network can be quickly conducted and visualized along side experimental results. By using the signaling network connectivity, analyses and predictions can be performed quickly using relatively easily constructed signaling network models. The application has been developed in Python and is designed to be easily extensible by groups interested in adding new or extending existing features. PathwayOracle is freely available for download and use.
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