Analysis and practical guideline of constraint-based boolean method in genetic network inference.

Boolean-based method, despite of its simplicity, would be a more attractive approach for inferring a network from high-throughput expression data if its effectiveness has not been limited by high false positive prediction. In this study, we explored factors that could simply be adjusted to improve t...

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Autores principales:	Treenut Saithong, Somkid Bumee, Chalothorn Liamwirat, Asawin Meechai
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ca0fb402461e4d4199d1e68d2432a445
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spelling	oai:doaj.org-article:ca0fb402461e4d4199d1e68d2432a4452021-11-18T07:30:06ZAnalysis and practical guideline of constraint-based boolean method in genetic network inference.1932-620310.1371/journal.pone.0030232https://doaj.org/article/ca0fb402461e4d4199d1e68d2432a4452012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22272315/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Boolean-based method, despite of its simplicity, would be a more attractive approach for inferring a network from high-throughput expression data if its effectiveness has not been limited by high false positive prediction. In this study, we explored factors that could simply be adjusted to improve the accuracy of inferring networks. Our work focused on the analysis of the effects of discretisation methods, biological constraints, and stringency of boolean function assignment on the performance of boolean network, including accuracy, precision, specificity and sensitivity, using three sets of microarray time-series data. The study showed that biological constraints have pivotal influence on the network performance over the other factors. It can reduce the variation in network performance resulting from the arbitrary selection of discretisation methods and stringency settings. We also presented the master boolean network as an approach to establish the unique solution for boolean analysis. The information acquired from the analysis was summarised and deployed as a general guideline for an efficient use of boolean-based method in the network inference. In the end, we provided an example of the use of such a guideline in the study of Arabidopsis circadian clock genetic network from which much interesting biological information can be inferred.Treenut SaithongSomkid BumeeChalothorn LiamwiratAsawin MeechaiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 1, p e30232 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Treenut Saithong Somkid Bumee Chalothorn Liamwirat Asawin Meechai Analysis and practical guideline of constraint-based boolean method in genetic network inference.
description	Boolean-based method, despite of its simplicity, would be a more attractive approach for inferring a network from high-throughput expression data if its effectiveness has not been limited by high false positive prediction. In this study, we explored factors that could simply be adjusted to improve the accuracy of inferring networks. Our work focused on the analysis of the effects of discretisation methods, biological constraints, and stringency of boolean function assignment on the performance of boolean network, including accuracy, precision, specificity and sensitivity, using three sets of microarray time-series data. The study showed that biological constraints have pivotal influence on the network performance over the other factors. It can reduce the variation in network performance resulting from the arbitrary selection of discretisation methods and stringency settings. We also presented the master boolean network as an approach to establish the unique solution for boolean analysis. The information acquired from the analysis was summarised and deployed as a general guideline for an efficient use of boolean-based method in the network inference. In the end, we provided an example of the use of such a guideline in the study of Arabidopsis circadian clock genetic network from which much interesting biological information can be inferred.
format	article
author	Treenut Saithong Somkid Bumee Chalothorn Liamwirat Asawin Meechai
author_facet	Treenut Saithong Somkid Bumee Chalothorn Liamwirat Asawin Meechai
author_sort	Treenut Saithong
title	Analysis and practical guideline of constraint-based boolean method in genetic network inference.
title_short	Analysis and practical guideline of constraint-based boolean method in genetic network inference.
title_full	Analysis and practical guideline of constraint-based boolean method in genetic network inference.
title_fullStr	Analysis and practical guideline of constraint-based boolean method in genetic network inference.
title_full_unstemmed	Analysis and practical guideline of constraint-based boolean method in genetic network inference.
title_sort	analysis and practical guideline of constraint-based boolean method in genetic network inference.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/ca0fb402461e4d4199d1e68d2432a445
work_keys_str_mv	AT treenutsaithong analysisandpracticalguidelineofconstraintbasedbooleanmethodingeneticnetworkinference AT somkidbumee analysisandpracticalguidelineofconstraintbasedbooleanmethodingeneticnetworkinference AT chalothornliamwirat analysisandpracticalguidelineofconstraintbasedbooleanmethodingeneticnetworkinference AT asawinmeechai analysisandpracticalguidelineofconstraintbasedbooleanmethodingeneticnetworkinference
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Analysis and practical guideline of constraint-based boolean method in genetic network inference.

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