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dc.contributor.authorWang, Hsiuyingen_US
dc.contributor.authorLu, Henry Horng-Shingen_US
dc.contributor.authorChueh, Tung-Hungen_US
dc.date.accessioned2014-12-08T15:33:14Z-
dc.date.available2014-12-08T15:33:14Z-
dc.date.issued2011-06-01en_US
dc.identifier.issn1932-6203en_US
dc.identifier.urihttp://dx.doi.org/10.1371/journal.pone.0020074en_US
dc.identifier.urihttp://hdl.handle.net/11536/23124-
dc.description.abstractNetworks are widely used in biology to represent the relationships between genes and gene functions. In Boolean biological models, it is mainly assumed that there are two states to represent a gene: on-state and off-state. It is typically assumed that the relationship between two genes can be characterized by two kinds of pairwise relationships: similarity and prerequisite. Many approaches have been proposed in the literature to reconstruct biological relationships. In this article, we propose a two-step method to reconstruct the biological pathway when the binary array data have measurement error. For a pair of genes in a sample, the first step of this approach is to assign counting numbers for every relationship and select the relationship with counting number greater than a threshold. The second step is to calculate the asymptotic p-values for hypotheses of possible relationships and select relationships with a large p-value. This new method has the advantages of easy calculation for the counting numbers and simple closed forms for the p-value. The simulation study and real data example show that the two-step counting method can accurately reconstruct the biological pathway and outperform the existing methods. Compared with the other existing methods, this two-step method can provide a more accurate and efficient alternative approach for reconstructing the biological network.en_US
dc.language.isoen_USen_US
dc.titleConstructing Biological Pathways by a Two-Step Counting Approachen_US
dc.typeArticleen_US
dc.identifier.doi10.1371/journal.pone.0020074en_US
dc.identifier.journalPLOS ONEen_US
dc.citation.volume6en_US
dc.citation.issue6en_US
dc.citation.epageen_US
dc.contributor.department統計學研究所zh_TW
dc.contributor.departmentInstitute of Statisticsen_US
dc.identifier.wosnumberWOS:000291309900001-
dc.citation.woscount3-
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