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

Paper ID Volume ID Publish Year Pages File Format Full-Text
15232 1394 2011 12 PDF Available
Title
Data-based modeling and prediction of cytotoxicity induced by contaminants in water resources
Abstract

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 (CI) have been recorded on-line as time series. The CI 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 CI 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.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideResearch highlights► We model dynamic cytotoxicity responses of living cells to 3 potential water toxicants. ► Support vector regression (SVR) is applied to develop nonlinear dynamic local models. ► The local SVR-based models demonstrate better predictive performance than the ANNs. ► The local SVR-based models are more robust to the increase of prediction horizons. ► SVR-based dynamic modeling has great potential in predicting cytotoxicity responses.

Keywords
Cytotoxicity monitoring; Cell population dynamic modeling; Support vector regression; Water protection; Early warning
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Data-based modeling and prediction of cytotoxicity induced by contaminants in water resources
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Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 35, Issue 2, April 2011, Pages 69–80
Authors
, , , , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us