Department of Mathematics, Box 480, Uppsala, SE-751 06, Sweden.
Mozilla Foundation, 2 Harrison Street, Suite 175, San Francisco, CA 94105, USA.
Math Biosci. 2023 Aug;362:109033. doi: 10.1016/j.mbs.2023.109033. Epub 2023 May 29.
We provide a critique of mathematical biology in light of rapid developments in modern machine learning. We argue that out of the three modelling activities - (1) formulating models; (2) analysing models; and (3) fitting or comparing models to data - inherent to mathematical biology, researchers currently focus too much on activity (2) at the cost of (1). This trend, we propose, can be reversed by realising that any given biological phenomenon can be modelled in an infinite number of different ways, through the adoption of a pluralistic approach, where we view a system from multiple, different points of view. We explain this pluralistic approach using fish locomotion as a case study and illustrate some of the pitfalls - universalism, creating models of models, etc. - that hinder mathematical biology. We then ask how we might rediscover a lost art: that of creative mathematical modelling.
我们根据现代机器学习的快速发展，对数学生物学进行了批判。我们认为，在数学生物学的三种建模活动（1）构建模型；（2）分析模型；（3）拟合或比较模型与数据中，研究人员目前过于关注活动（2），而忽略了活动（1）。我们提出，这种趋势可以通过认识到任何给定的生物学现象都可以通过采用多元化的方法，以无限种不同的方式建模来扭转，我们从多个不同的角度来看待一个系统。我们使用鱼类运动作为案例研究来解释这种多元化方法，并说明了一些阻碍数学生物学的陷阱——普遍主义、创建模型的模型等。然后，我们问如何重新发现一种失落的艺术：创造性的数学建模。
