Data-based modeling and prediction of cytotoxicity induced by contaminants in water resources

作者：Khatibisepehr S; Huang B^*; Ibrahim F; Xing J Z; Roa W

来源：Computational Biology and Chemistry, 2011, 35(2): 69-80.

DOI：10.1016/j.compbiolchem.2011.02.001

• Cytotoxicity monitoring
• Cell population dynamic modeling
• Support vector regression
• Water protection
• Early warning

This paper is concerned with dynamic modeling, prediction and analysis of cell cytotoxicity induced by water contaminants. A real-time cell electronic sensing (RT-CES) system has been used for continuously monitoring dynamic cytotoxicity responses of living cells. Cells are grown onto the surfaces of the microelectronic sensors. Changes in cell number expressed as cell index (Cl) have been recorded on-line as time series. The Cl data are used to develop dynamic prediction models for cell cytotoxicity process. We consider support vector regression (SVR) algorithm to implement data-based system identification for dynamic modeling and prediction of cytotoxicity. Through several validation studies, multi-step-ahead predictions are calculated and compared with the actual Cl obtained from experiments. It is shown that SVR-based dynamic modeling has great potential in predicting the cytotoxicity response of the cells in the presence of toxicant.

• 出版日期2011-4