Inference of Genetic Network of Xenopus Frog Egg : Improved Genetic Algorithm

Author

Wu, Shinq-Jen ; Chou, Chia-Hsien ; Wu, Cheng-Tao ; Lee, Tsu-Tian

Author_Institution

Dept. of Electr. Eng., Da-Yeh Univ., Chang-Hwa

fYear

2006

fDate

Aug. 30 2006-Sept. 3 2006

Firstpage

4147

Lastpage

4150

Abstract

An improved genetic algorithm (IGA) is proposed to achieve 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 interaction 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 achieve 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

Keywords

biology computing; cellular biophysics; genetic algorithms; genetics; Cdc25; Michaelis-Menten model; S-system genetic network; Xenopus frog egg; cell-cycle control; chromosome; cyclin-Cdc2; gene regulatory networks; improved genetic algorithm; mitotic control; time-courses training datasets; Bayesian methods; Biological system modeling; Biological systems; Cities and towns; Control engineering; Evolution (biology); Genetic algorithms; Genetic programming; Power system modeling; USA Councils; IGA; Michaelis-Menten model; S-system; Xenopus frog egg cell cycle;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE

Conference_Location

New York, NY

ISSN

1557-170X

Print_ISBN

1-4244-0032-5

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2006.260227

Filename

4462714