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Validation of a Morphogenesis Model of Drosophila Early Development by a Multi-objective Evolutionary Optimization Algorithm

机译:果蝇早期发育的形态发生模型的多目标进化优化算法验证

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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 Bi-coid 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 multi-objective 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.
机译:我们应用进化计算来校准果蝇早期发育的形态发生模型的参数。该模型旨在描述果蝇胚胎前后轴上的双壳蛋白和尾蛋白稳定梯度的建立。模型方程由具有初始和零通量边界条件的非线性抛物线偏微分方程组组成。我们将CMA-ES算法的单目标变体和多目标变体的结果与实验数据进行比较,以进行模型校准。尽管多目标算法计算了Pareto前沿的完全近似值,但单目标算法的重复运行给出了(在Pareto意义上)支配多目标方法结果的解决方案。我们保留通过后一种技术找到的最佳解决方案。从生物学的角度来看,所有这些解决方案都是同样可以接受的,对于我们的测试案例,帕累托前沿的实验数据和经过验证的模型解决方案之间的相对误差在3%-6%的范围内。此技术是通用技术,可以用作参数校准问题的通用工具。

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