An Introduction to Genetic Algorithms
An Introduction to Genetic Algorithms
Membrane Computing: An Introduction
Membrane Computing: An Introduction
System Modeling in Cellular Biology: From Concepts to Nuts and Bolts
System Modeling in Cellular Biology: From Concepts to Nuts and Bolts
The metabolic algorithm for P systems: Principles and applications
Theoretical Computer Science
Learning regulation functions of metabolic systems by artificial neural networks
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Data analysis pipeline from laboratory to MP models
Natural Computing: an international journal
A methodology based on MP theory for gene expression analysis
CMC'11 Proceedings of the 12th international conference on Membrane Computing
A genetic approach for synthesizing metabolic models from time series
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
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Metabolic P systems are a modeling framework for metabolic, regulatory and signaling processes. The synthesis of flux regulation functions from time series of substance concentrations is a key task for reverse-engineering biological systems by MP systems. In this paper we present some important improvements to a technique based on genetic algorithms and multiple linear regression for the synthesis of regulation functions. An accurate analysis of generated functions, for the case study of the mitotic oscillator in early amphibian embryos, shows that some knowledge about the regulation mechanisms of biological processes can be inferred from experimental data using this methodology.