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

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2003

Autores

J. Peres (Autor) FEUP; Oliveira, R (Autor) Outra; S. Feyo de Azevedo (Autor) FEUP

Ata de Conferência Internacional

Título: EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING - 13

Páginas: 839-844

13th European Symposium on Computer Aided Process Engineering (ESCAPE-13)

LAPPEENRANTA, FINLAND, JUN 01-04, 2003

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-000-JM9

DOI: 10.1016/s1570-7946(03)80221-3

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6