Evidence map›Paper›PMID 22536967›Full record

ArticleBMC bioinformatics2012

Modeling gene regulatory network motifs using Statecharts.

Fabio Fioravanti, Manuela Helmer-Citterich, Enrico Nardelli

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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.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
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3 · Its place in the literature

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6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Fabio FioravantiDepartment of Biology, University of Rome Tor Vergata, Rome I-00133, Italy.
Manuela Helmer-Citterich
Enrico Nardelli

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Gene Regulatory NetworksSoftwareEscherichia coliModels, BiologicalSystems Biology

Identifiers

PMID22536967
PMCPMC3434443

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.