一个数据驱动的框架来建模生物-环境系统
Lisandro Milocco1, Tobias Uller1
1Department of Biology, Lund University, Lund, Sweden.
Evolution & development
|June 6, 2023
概括
有机体和它们的环境有动态的相互作用. 这项研究提出了一个新的建模框架,用于预测生物如何对环境变化做出反应,即使它们随着时间的推移而发展.
科学领域:
- 发育生物学是发展生物学.
- 生态生态学 生态生态学
- 系统生物学 系统生物学
背景情况:
- 生物不断与环境相互作用和改变它们,这是一个复杂的动态,难以建模.
- 对于像表型可塑性这样的现象,需要准确的模型,从而能够预测生物体对环境信号的反应.
- 现有的模型往往难以捕捉生物体与环境相互作用的结合性,并与现实世界的数据相配合.
研究的目的:
- 为结合生物与环境系统引入一个新的建模框架.
- 为了能够对有机体如何随着时间的推移对环境信号做出反应进行定量预测.
- 将表型可塑性建模为一个动态的,发育调节的属性.
主要方法:
- 开发了一个非线性黑盒模型框架,将生物体和环境表示为单一合的动态系统.
- 利用时间序列输入 (环境信号) 和输出 (系统测量) 数据以适应模型.
- 用于in silico实验来测试框架对表型可塑性的预测能力.
主要成果:
- 该框架成功地捕捉了生物体与环境相互作用的动态性质.
- 该模型可以使用观测数据来安装,并且在没有深入的系统特定知识的情况下应用.
- 证明了对新型环境信号的生物反应的准确预测 in silico.
- 表明,表型可塑性可以作为在本体发生过程中的时间变化的动态性质进行建模.
结论:
- 拟议的框架为研究生物-环境动态和表型可塑性提供了一个强大的工具.
- 它允许在整个发展过程中对复杂的生物系统进行数据驱动的预测建模.
- 这种方法提升了我们对环境相互作用如何塑造生物体的发展和随着时间的推移而起作用的理解.
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