Modelling cells reaction kinetics with artificial neural networks: A comparison of three network architectures

J. Peres, R. Oliveira, S. Feyo de Azevedo

Research output: Contribution to journalArticle

Abstract

The present work compares three neural network architectures for modelling reaction kinetics in biological systems: the Mixture of Experts (ME) network, the Backpropagation (BP) network and the Radial Basis Function (RBF) network. The methods are outlined for the case of the growth kinetics of the Saccharomyces cerevisae yeast. The S. cerevisae yeast is able to grow through 3 different pathways. The main results show that a ME network with 3 linear expert modules was able to discriminate between the 3 pathways. The network was trained with the Expectation Maximisation method. A Gaussian gating system produced three input space partitions, one for each of the pathways. The 3 expert modules developed expertise in describing the kinetics of each of the pathways.

Original languageEnglish
Pages (from-to)839-844
Number of pages6
JournalComputer Aided Chemical Engineering
Volume14
Issue numberC
DOIs
Publication statusPublished - 1 Dec 2003

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