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dc.contributor.authorWu, Shinq-Jenen_US
dc.contributor.authorChou, Chia-Hsienen_US
dc.contributor.authorWu, Cheng-Taoen_US
dc.contributor.authorLee, Tsu-Tianen_US
dc.date.accessioned2017-04-21T06:48:31Z-
dc.date.available2017-04-21T06:48:31Z-
dc.date.issued2006en_US
dc.identifier.isbn978-1-4244-0032-4en_US
dc.identifier.urihttp://hdl.handle.net/11536/135184-
dc.description.abstractAn improved genetic algorithm (IGA) is proposed to acheive S-system gene network modeling of Xenopus frog egg. Via the time-courses training datasets from Michaelis-Menten model, the optimal parameters are learned. The S-system can clearly describe activative and inhibitory interacation between genes as generating and consuming process. We concern the mitotic control in cell-cycle of Xenopus frog egg to realize cyclin-Cdc2 and Cdc25 for MPF activity. The proposed IGA can acheive global search with migration and keep the best chromosome with elitism operation. The generated gene regulatory networks can provide biological researchers for further experiments in Xenopus frog egg cell cycle control.en_US
dc.language.isoen_USen_US
dc.subjectIGAen_US
dc.subjectMichaelis-Menten modelen_US
dc.subjectS-systemen_US
dc.subjectxenopusen_US
dc.subjectfrog egg cell cycleen_US
dc.titleInference of genetic network of Xenopus frog egg: Improved genetic algorithmen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2006 28TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-15en_US
dc.citation.spage1373en_US
dc.citation.epage+en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000247284701128en_US
dc.citation.woscount0en_US
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