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Rethinking Causation for Data-intensive Biology: Constraints, Cancellations, and Quantized Organisms: Causality in complex organisms is sculpted by constraints rather than instigators, with outcomes perhaps better described by quantized patterns than rectilinear pathways.
BioEssays ( IF 3.2 ) Pub Date : 2020-06-02 , DOI: 10.1002/bies.201900135 Douglas E Brash 1
BioEssays ( IF 3.2 ) Pub Date : 2020-06-02 , DOI: 10.1002/bies.201900135 Douglas E Brash 1
Affiliation
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Complex organisms thwart the simple rectilinear causality paradigm of “necessary and sufficient,” with its experimental strategy of “knock down and overexpress.” This Essay organizes the eccentricities of biology into four categories that call for new mathematical approaches; recaps for the biologist the philosopher's recent refinements to the causation concept and the mathematician's computational tools that handle some but not all of the biological eccentricities; and describes overlooked insights that make causal properties of physical hierarchies such as emergence and downward causation straightforward. Reviewing and extrapolating from similar situations in physics, it is suggested that new mathematical tools for causation analysis incorporating feedback, signal cancellation, nonlinear dependencies, physical hierarchies, and fixed constraints rather than instigative changes will reveal unconventional biological behaviors. These include “eigenisms,” organisms that are limited to quantized states; trajectories that steer a system such as an evolving species toward optimal states; and medical control via distributed “sheets” rather than single control points.
中文翻译：
重新思考数据密集型生物学的因果关系：约束、取消和量化有机体：复杂有机体中的因果关系是由约束而不是煽动者塑造的，用量化模式比直线路径可能更好地描述结果。
复杂的生物体以其“击倒和过度表达”的实验策略阻碍了“必要和充分”的简单直线因果关系范式。这篇文章将生物学的怪异现象分为四类，需要新的数学方法；为生物学家回顾哲学家最近对因果关系概念的改进以及数学家处理部分但不是全部生物学怪异现象的计算工具；并描述了被忽视的见解，这些见解使物理层次结构的因果特性（例如出现和向下因果关系）变得简单明了。回顾和推断物理学中的类似情况，建议用于因果分析的新数学工具结合反馈、信号消除、非线性依赖性、物理层次结构和固定约束而不是激发变化，将揭示非常规的生物行为。其中包括“本征论”，即仅限于量子态的有机体；引导系统（例如进化物种）走向最佳状态的轨迹；通过分布式“表”而不是单个控制点进行医疗控制。
更新日期：2020-06-29
中文翻译：
重新思考数据密集型生物学的因果关系：约束、取消和量化有机体：复杂有机体中的因果关系是由约束而不是煽动者塑造的，用量化模式比直线路径可能更好地描述结果。
复杂的生物体以其“击倒和过度表达”的实验策略阻碍了“必要和充分”的简单直线因果关系范式。这篇文章将生物学的怪异现象分为四类，需要新的数学方法；为生物学家回顾哲学家最近对因果关系概念的改进以及数学家处理部分但不是全部生物学怪异现象的计算工具；并描述了被忽视的见解，这些见解使物理层次结构的因果特性（例如出现和向下因果关系）变得简单明了。回顾和推断物理学中的类似情况，建议用于因果分析的新数学工具结合反馈、信号消除、非线性依赖性、物理层次结构和固定约束而不是激发变化，将揭示非常规的生物行为。其中包括“本征论”，即仅限于量子态的有机体；引导系统（例如进化物种）走向最佳状态的轨迹；通过分布式“表”而不是单个控制点进行医疗控制。
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