Biomaterial Database

Genetic programming as an analytical tool for non-linear dielectric spectroscopy. 1999

A M Woodward, and R J Gilbert, and D B Kell

Institute of Biological Sciences, University of Wales, Aberystwyth, Ceredigion, UK. azw@aber.ac.uk

By modelling the non-linear effects of membranous enzymes on an applied oscillating electromagnetic field using supervised multivariate analysis methods, Non-Linear Dielectric Spectroscopy (NLDS) has previously been shown to produce quantitative information that is indicative of the metabolic state of various organisms. The use of Genetic Programming (GP) for the multivariate analysis of NLDS data recorded from yeast fermentations is discussed, and GPs are compared with previous results using Partial Least Squares (PLS) and Artificial Neural Nets (NN). GP considerably outperforms these methods, both in terms of the precision of the predictions and their interpretability.

UI	MeSH Term	Description	Entries
D008957	Models, Genetic	Theoretical representations that simulate the behavior or activity of genetic processes or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.	Genetic Models,Genetic Model,Model, Genetic
D005285	Fermentation	Anaerobic degradation of GLUCOSE or other organic nutrients to gain energy in the form of ATP. End products vary depending on organisms, substrates, and enzymatic pathways. Common fermentation products include ETHANOL and LACTIC ACID.	Fermentations
D013057	Spectrum Analysis	The measurement of the amplitude of the components of a complex waveform throughout the frequency range of the waveform. (McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed)	Spectroscopy,Analysis, Spectrum,Spectrometry
D016571	Neural Networks, Computer	A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.	Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron
D055672	Static Electricity	The accumulation of an electric charge on a object	Electrostatic,Electrostatics,Static Charge,Charge, Static,Charges, Static,Electricity, Static,Static Charges
D019295	Computational Biology	A field of biology concerned with the development of techniques for the collection and manipulation of biological data, and the use of such data to make biological discoveries or predictions. This field encompasses all computational methods and theories for solving biological problems including manipulation of models and datasets.	Bioinformatics,Molecular Biology, Computational,Bio-Informatics,Biology, Computational,Computational Molecular Biology,Bio Informatics,Bio-Informatic,Bioinformatic,Biologies, Computational Molecular,Biology, Computational Molecular,Computational Molecular Biologies,Molecular Biologies, Computational