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A study of parallel and evolutionary framework for modelling biochemical signalling pathways

机译:对生物化学信号传导途径建模的平行和进化框架的研究

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Modelling biochemical pathways provides an opportunity for scientists and engineers from biochemistry, computer science and mathematics areas to work together in the area of computational biology. Due to the complexity of biochemical pathways, it is natural to employ a parallel and evolutionary modelling approach to composing target biochemical signalling pathways. In this research, a parallel and evolutionary modelling framework is proposed to construct models for biochemical pathways. An evolutionary method is employed to develop biochemical components by generic operators and suggested composition rules, and then a global search approach is used to explore kinetic rate values in the model candidates. Information of species behaviours and interactions among the species in given target biochemical pathways is referred to drive the model constructions. Simulation results show that the modelling framework is feasible to explore the biochemical model structure space and obtain biochemical reactants performing discover of biochemical elements in the target pathways. evolution strategy; simulated annealing.
机译:对生化途径进行建模为来自生物化学,计算机科学和数学领域的科学家和工程师提供了在计算生物学领域进行合作的机会。由于生化途径的复杂性,自然采用并行且进化的建模方法来构成目标生化信号传导途径。在这项研究中,提出了一个并行且进化的建模框架来构建生化途径的模型。通过通用算子和建议的组成规则,采用进化方法来开发生化成分,然后使用全局搜索方法来探索候选模型中的动力学速率值。在给定的目标生化途径中,物种行为和物种间相互作用的信息被用来驱动模型的构建。仿真结果表明,该建模框架对于探索生化模型结构空间并获得在目标途径中发现生化元素的生化反应物是可行的。进化策略;模拟退火。

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