Title :
Robustness Analysis of EGFR Signaling Network Based on Evolutionary Algorithm
Author :
Wang, Ting ; Zou, Xiufen
Author_Institution :
Sch. of Math. Phys. & Inf. Sci., Zhejiang Ocean Univ., Zhoushan
Abstract :
The epidermal growth factor receptor (EGFR) is constitutively activated in a variety of human malignancies. The redundant expression and mutation of EGFR can bring on uncontrollable cell growth, and then form tumor. Here, the paper firstly demonstrates the EGFR signaling network is robust with respect to its "signal time", "signal duration" and "signal amplitude" by simulations. Furthermore, the paper uses evolutionary algorithm to optimize the robustness of the EGER signaling network and obtains two groups of rate constants at which the robustness of signal time and signal amplitude are best in a certain parameter range. The results indicate the optimized rate constants make the stability of the three signal features of the network be improved remarkably.
Keywords :
cancer; cellular biophysics; evolutionary computation; medical computing; patient treatment; skin; tumours; cancer treatment; epidermal growth factor receptor signaling network; evolutionary algorithm; human malignancy; rate constants; robustness analysis; signal transduction; uncontrollable cell growth; Algorithm design and analysis; Biological systems; Breast neoplasms; Cancer; Evolutionary computation; Mathematical model; Mathematics; Medical treatment; Robustness; Signal analysis;
Conference_Titel :
Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1747-6
Electronic_ISBN :
978-1-4244-1748-3
DOI :
10.1109/ICBBE.2008.229