MacLeod Miles, Nersessian Nancy J
Department of Philosophy, University of Twente, Drienerlolaan 5, 7522 NB, Enschede, The Netherlands.
Department of Psychology, Harvard University, 33 Kirkland St., Cambridge, MA, 02138, USA.
Hist Philos Life Sci. 2018 Jan 8;40(1):17. doi: 10.1007/s40656-017-0183-9.
Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations.
现代整合系统生物学是通过计算建模和模拟来处理复杂问题的方式来定义自身的。然而，在整合系统生物学中，计算机并非独自解决问题。解决问题一如既往地依赖于人类认知资源。当前的哲学解释暗示了它们的重要性，但人类认知在计算建模中扮演何种角色仍有待理解。在本文中，我们关注系统生物学建模者通过计算模拟和其他工具来处理建模问题的认知复杂性，以便能够对理解、干预和控制复杂生物系统做出重大贡献的实践。因此，我们展示了认知，尤其是模拟心理建模过程，如何在模型构建过程中发挥核心作用。同时，我们提出系统生物学中关于建模内容的表征选择是如何因此受到限制或约束的。这些约束有助于我们理解和合理化该领域中问题解决所采用的受限形式，以及为何其结果并不总是符合预期。
