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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doaj-ca0fb402461e4d4199d1e68d2432a4452021-03-03T20:30:40ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0171e3023210.1371/journal.pone.0030232Analysis and practical guideline of constraint-based boolean method in genetic network inference.Treenut SaithongSomkid BumeeChalothorn LiamwiratAsawin MeechaiBoolean-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.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22272315/pdf/?tool=EBI |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Treenut Saithong Somkid Bumee Chalothorn Liamwirat Asawin Meechai |
spellingShingle |
Treenut Saithong Somkid Bumee Chalothorn Liamwirat Asawin Meechai Analysis and practical guideline of constraint-based boolean method in genetic network inference. PLoS ONE |
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) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2012-01-01 |
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. |
url |
https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22272315/pdf/?tool=EBI |
work_keys_str_mv |
AT treenutsaithong analysisandpracticalguidelineofconstraintbasedbooleanmethodingeneticnetworkinference AT somkidbumee analysisandpracticalguidelineofconstraintbasedbooleanmethodingeneticnetworkinference AT chalothornliamwirat analysisandpracticalguidelineofconstraintbasedbooleanmethodingeneticnetworkinference AT asawinmeechai analysisandpracticalguidelineofconstraintbasedbooleanmethodingeneticnetworkinference |
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