Validation of a morphogenesis Model of Drosophila Early Development by a Multi-objective evolutionary Optimization Algorithm

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Title: Validation of a morphogenesis Model of Drosophila Early Development by a Multi-objective evolutionary Optimization Algorithm
Authors: Dilão, Rui
Muraro, Daniele
Nicolau, Miguel
Schoenauer, Marc
Permanent link: http://hdl.handle.net/10197/8294
Date: 17-Apr-2009
Abstract: We apply evolutionary computation to calibrate the parameters of a morphogenesis model of Drosophila early development. The model aims to describe the establishment of the steady gradients of Bicoid and Caudal proteins along the antero-posterior axis of the embryo of Drosophila. The model equations consist of a system of non-linear parabolic partial differential equations with initial and zero flux boundary conditions. We compare the results of single- and multi-objective variants of the CMA-ES algorithm for the model the calibration with the experimental data. Whereas the multiobjective algorithm computes a full approximation of the Pareto front, repeated runs of the single-objective algorithm give solutions that dominate (in the Pareto sense) the results of the multi-objective approach. We retain as best solutions those found by the latter technique. From the biological point of view, all such solutions are all equally acceptable, and for our test cases, the relative error between the experimental data and validated model solutions on the Pareto front are in the range 3% − 6%. This technique is general and can be used as a generic tool for parameter calibration problems.
Type of material: Conference Publication
Publisher: Springer
Copyright (published version): 2009 Springer
Keywords: Evolutionary algorithmsModel calibration
DOI: 10.1007/978-3-642-01184-9_16
Language: en
Status of Item: Peer reviewed
Is part of: Pizzuti, C., Ritchie, M.D. and Giacobini, M. (eds.). Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (Lectures Notes in Computer Science Volume 5843)
Conference Details: 7th European Conference: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2009, Tubingen, Germany, 15-17 April 2009
Appears in Collections:Business Research Collection

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