生命物理学理论的雄心壮志

IF 4.6 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY SciPost Physics Pub Date : 2024-08-15 DOI:10.21468/scipostphyslectnotes.84
William Bialek
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引用次数: 0

摘要

一个多世纪以来,理论物理学家一直对生命现象着迷。然而,当我们对生命系统进行更现实的描述时,情况变得复杂起来。在回顾了对这种复杂性的不同反应之后,我探讨了信息流优化这一潜在的通用理论原则。主要的例子是指导苍蝇胚胎发育的遗传网络,但每个想法也都通过神经系统的例子来说明。在每种情况下,优化都能做出详细的、基本不含参数的预测,并与实验进行定量联系。
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Ambitions for theory in the physics of life
Theoretical physicists have been fascinated by the phenomena of life for more than a century. As we engage with more realistic descriptions of living systems, however, things get complicated. After reviewing different reactions to this complexity, I explore the optimization of information flow as a potentially general theoretical principle. The primary example is a genetic network guiding development of the fly embryo, but each idea also is illustrated by examples from neural systems. In each case, optimization makes detailed, largely parameter-free predictions that connect quantitatively with experiment.
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来源期刊
SciPost Physics
SciPost Physics Physics and Astronomy-Physics and Astronomy (all)
CiteScore
8.20
自引率
12.70%
发文量
315
审稿时长
10 weeks
期刊介绍: SciPost Physics publishes breakthrough research articles in the whole field of Physics, covering Experimental, Theoretical and Computational approaches. Specialties covered by this Journal: - Atomic, Molecular and Optical Physics - Experiment - Atomic, Molecular and Optical Physics - Theory - Biophysics - Condensed Matter Physics - Experiment - Condensed Matter Physics - Theory - Condensed Matter Physics - Computational - Fluid Dynamics - Gravitation, Cosmology and Astroparticle Physics - High-Energy Physics - Experiment - High-Energy Physics - Theory - High-Energy Physics - Phenomenology - Mathematical Physics - Nuclear Physics - Experiment - Nuclear Physics - Theory - Quantum Physics - Statistical and Soft Matter Physics.
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