An introduction to genetic algorithms
An introduction to genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Membrane Computing: An Introduction
Membrane Computing: An Introduction
Probabilistic model checking in practice: case studies with PRISM
ACM SIGMETRICS Performance Evaluation Review
Systems Biology: Properties of Reconstructed Networks
Systems Biology: Properties of Reconstructed Networks
System Modeling in Cellular Biology: From Concepts to Nuts and Bolts
System Modeling in Cellular Biology: From Concepts to Nuts and Bolts
P systems, a new computational modelling tool for systems biology
Transactions on Computational Systems Biology VI
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
IEEE Transactions on Evolutionary Computation
A Multiscale Modeling Framework Based on P Systems
Membrane Computing
MetaPlab: A Computational Framework for Metabolic P Systems
Membrane Computing
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Learning regulation functions of metabolic systems by artificial neural networks
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
An Approach to the Engineering of Cellular Models Based on P Systems
CiE '09 Proceedings of the 5th Conference on Computability in Europe: Mathematical Theory and Computational Practice
Deterministic and stochastic P systems for modelling cellular processes
Natural Computing: an international journal
Evolutionary symbolic discovery for bioinformatics, systems and synthetic biology
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Target driven biochemical network reconstruction based on petri nets and simulated annealing
Proceedings of the 8th International Conference on Computational Methods in Systems Biology
Regulation and covering problems in MP systems
WMC'09 Proceedings of the 10th international conference on Membrane Computing
Tuning p systems for solving the broadcasting problem
WMC'09 Proceedings of the 10th international conference on Membrane Computing
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In this work we present a new methodology for structure and parameter estimation in cell systems biology modelling. Our modelling framework is based on P systems, an unconventional computational paradigm that abstracts from the structure and functioning of the living cell. The process of designing models, consisting of both the optimisation of the modular structure and of the stochastic kinetic parameters, is performed using a memetic algorithm. Specically, we use a nested evolutionary algorithm where the first layer evolves rule structures while the inner layer, implemented also as a genetic algorithm (GA), fine tunes the parameters of the model. Our approach consists of an incremental methodology. Starting from very simple P system modules specifying basic molecular interactions, more complicated modules are produced to model more complex molecular systems. These newly found modules are in turn added to the library of available P systems modules so as to be used subsequently to develop more intricate and circuitous cellular models. The effectiveness of the algorithm was tested on three case studies, namely, molecular complexation, enzymatic reactions and autoregulation in transcriptional networks.