ArticleBMC bioinformatics2012
Modeling gene regulatory network motifs using Statecharts.
Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Detection of network motifs using three-way ANOVA.PloS one · 2018Article
- Systematic synergy modeling: understanding drug synergy from a systems biology perspective.BMC systems biology · 2015Article
- Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis.Journal of the Royal Society, Interface · 2014Article
- Computational analyses of synergism in small molecular network motifs.PLoS computational biology · 2014Article
- Reducing the complexity of complex gene coexpression networks by coupling multiweighted labeling with topological analysis.BioMed research international · 2013Article
- Bioinformatics in Italy: BITS2011, the Eighth Annual Meeting of the Italian Society of Bioinformatics.BMC bioinformatics · 2012Article
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3 authors.
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Abstract
backgroundGene regulatory networks are widely used by biologists to describe the interactions among genes, proteins and other components at the intra-cellular level. Recently, a great effort has been devoted to give gene regulatory networks a formal semantics based on existing computational frameworks.For this purpose, we consider Statecharts, which are a modular, hierarchical and executable formal model widely used to represent software systems. We use Statecharts for modeling small and recurring patterns of interactions in gene regulatory networks, called motifs.
resultsWe present an improved method for modeling gene regulatory network motifs using Statecharts and we describe the successful modeling of several motifs, including those which could not be modeled or whose models could not be distinguished using the method of a previous proposal.We model motifs in an easy and intuitive way by taking advantage of the visual features of Statecharts. Our modeling approach is able to simulate some interesting temporal properties of gene regulatory network motifs: the delay in the activation and the deactivation of the "output" gene in the coherent type-1 feedforward loop, the pulse in the incoherent type-1 feedforward loop, the bistability nature of double positive and double negative feedback loops, the oscillatory behavior of the negative feedback loop, and the "lock-in" effect of positive autoregulation.
conclusionsWe present a Statecharts-based approach for the modeling of gene regulatory network motifs in biological systems. The basic motifs used to build more complex networks (that is, simple regulation, reciprocal regulation, feedback loop, feedforward loop, and autoregulation) can be faithfully described and their temporal dynamics can be analyzed.
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