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

机译:多目标进化优化算法验证果蝇早期发展的形态发生模型

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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:我们应用进化计算以校准果蝇早期发展的形态发生模型的参数。该模型旨在描述沿果蝇的胚胎的翼形后轴的双核糖和尾蛋白的稳定梯度建立。模型方程由具有初始和零通量边界条件的非线性抛物面部分微分方程的系统组成。我们将CMA-ES算法的单级和多目标变体的结果进行比较,以便使用实验数据模型校准。虽然多目标算法计算了帕累托前线的全近似,但重复运行的单目标算法提供了占主导地位的解决方案(在Pareto Sense中)多目标方法的结果。我们保留了后一种技术发现的最佳解决方案。从生物学的角度来看,所有这些解决方案都是同样可接受的,对于我们的测试用例,帕累托前线的实验数据和验证模型解决方案之间的相对误差在3%-6%范围内。该技术是通用的,可以用作参数校准问题的通用工具。

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