Determining whether and how a gene is transcribed are two of the central processes of life. The conceptual basis for understanding such gene regulation arose from pioneering biophysical studies in eubacteria. However, eukaryotic genomes exhibit vastly greater complexity, which raises questions not addressed by this bacterial paradigm. First, how is information integrated from many widely separated binding sites to determine how a gene is transcribed? Second, does the presence of multiple energy-expending mechanisms, which are absent from eubacterial genomes, indicate that eukaryotes are capable of improved forms of genetic information processing? An updated biophysical foundation is needed to answer such questions. We describe the linear framework, a graph-based approach to Markov processes, and show that it can accommodate many previous studies in the field. Under the assumption of thermodynamic equilibrium, we introduce a language of higher-order cooperativities and show how it can rigorously quantify gene regulatory properties suggested by experiment. We point out that fundamental limits to information processing arise at thermodynamic equilibrium and can only be bypassed through energy expenditure. Finally, we outline some of the mathematical challenges that must be overcome to construct an improved biophysical understanding of gene regulation.

中文翻译：

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平衡内外的基因调控。

确定基因是否被转录以及如何转录是生命的两个主要过程。了解这种基因调控的概念基础来自于先导性的真细菌生物物理研究。然而，真核生物基因组显示出极大的复杂性，这提出了该细菌范式未解决的问题。首先，如何从许多广泛分离的结合位点整合信息以确定基因如何转录？其次，真细菌基因组中不存在多种耗能机制，是否表明真核生物能够改善遗传信息处理的形式？需要更新的生物物理基础来回答这些问题。我们描述了线性框架，一种基于图的马尔可夫过程，并表明它可以适应该领域以前的许多研究。在热力学平衡的假设下，我们引入了一种高阶合作性语言，并展示了它如何能够严格量化实验建议的基因调控特性。我们指出，信息处理的基本限制出现在热力学平衡上，并且只能通过能量消耗来绕开。最后，我们概述了在构建对基因调控的生物物理认识方面必须克服的一些数学挑战。我们指出，信息处理的基本限制出现在热力学平衡上，并且只能通过能量消耗来绕开。最后，我们概述了在构建对基因调控的生物物理认识方面必须克服的一些数学挑战。我们指出，信息处理的基本限制出现在热力学平衡上，并且只能通过能量消耗来绕开。最后，我们概述了在构建对基因调控的生物物理认识方面必须克服的一些数学挑战。