Statecharts for gene network modeling.

State diagrams (stategraphs) are suitable for describing the behavior of dynamic systems. However, when they are used to model large and complex systems, determining the states and transitions among them can be overwhelming, due to their flat, unstratified structure. In this article, we present the...

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Main Authors: Yong-Jun Shin, Mehrdad Nourani
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2010-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC2826420?pdf=render
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spelling doaj-5fc1fb2af0f5443aa28fa780ffa943292020-11-25T01:57:54ZengPublic Library of Science (PLoS)PLoS ONE1932-62032010-01-0152e937610.1371/journal.pone.0009376Statecharts for gene network modeling.Yong-Jun ShinMehrdad NouraniState diagrams (stategraphs) are suitable for describing the behavior of dynamic systems. However, when they are used to model large and complex systems, determining the states and transitions among them can be overwhelming, due to their flat, unstratified structure. In this article, we present the use of statecharts as a novel way of modeling complex gene networks. Statecharts extend conventional state diagrams with features such as nested hierarchy, recursion, and concurrency. These features are commonly utilized in engineering for designing complex systems and can enable us to model complex gene networks in an efficient and systematic way. We modeled five key gene network motifs, simple regulation, autoregulation, feed-forward loop, single-input module, and dense overlapping regulon, using statecharts. Specifically, utilizing nested hierarchy and recursion, we were able to model a complex interlocked feed-forward loop network in a highly structured way, demonstrating the potential of our approach for modeling large and complex gene networks.http://europepmc.org/articles/PMC2826420?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Yong-Jun Shin
Mehrdad Nourani
spellingShingle Yong-Jun Shin
Mehrdad Nourani
Statecharts for gene network modeling.
PLoS ONE
author_facet Yong-Jun Shin
Mehrdad Nourani
author_sort Yong-Jun Shin
title Statecharts for gene network modeling.
title_short Statecharts for gene network modeling.
title_full Statecharts for gene network modeling.
title_fullStr Statecharts for gene network modeling.
title_full_unstemmed Statecharts for gene network modeling.
title_sort statecharts for gene network modeling.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2010-01-01
description State diagrams (stategraphs) are suitable for describing the behavior of dynamic systems. However, when they are used to model large and complex systems, determining the states and transitions among them can be overwhelming, due to their flat, unstratified structure. In this article, we present the use of statecharts as a novel way of modeling complex gene networks. Statecharts extend conventional state diagrams with features such as nested hierarchy, recursion, and concurrency. These features are commonly utilized in engineering for designing complex systems and can enable us to model complex gene networks in an efficient and systematic way. We modeled five key gene network motifs, simple regulation, autoregulation, feed-forward loop, single-input module, and dense overlapping regulon, using statecharts. Specifically, utilizing nested hierarchy and recursion, we were able to model a complex interlocked feed-forward loop network in a highly structured way, demonstrating the potential of our approach for modeling large and complex gene networks.
url http://europepmc.org/articles/PMC2826420?pdf=render
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