Title :
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
fDate :
Aug. 30 2006-Sept. 3 2006
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;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.260227
