Inference of genetic network of Xenopus frog egg: improved genetic algorithm.
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.
Wu
Shinq-Jen
SJ
Dept. of Electr. Eng., Da-Yeh Univ., Chang-Hwa, Taiwan. jen@cn.nctu.edu.tw
Chou
Chia-Hsien
CH
Wu
Cheng-Tao
CT
Lee
Tsu-Tian
TT
D000465:Algorithms; D000818:Animals; D018797:Cell Cycle Proteins / Q000235:genetics; D019143:Evolution, Molecular; D005260:Female; D005786:Gene Expression Regulation; D008957:Models, Genetic; D010063:Ovum / Q000502:physiology*; D011494:Protein Kinases / Q000235:genetics; D014981:Xenopus / Q000235:genetics* / Q000502:physiology; D029867:Xenopus Proteins / Q000235:genetics; D020687:cdc25 Phosphatases / Q000235:genetics
D018797:Cell Cycle Proteins; D029867:Xenopus Proteins; D011494:Protein Kinases; C070577:CDK1 protein, Xenopus; D020687:cdc25 Phosphatases