Optimization of Transcription Factor Genetic Circuits
Optimization of Transcription Factor Genetic Circuits
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DOI：
10.1101/2022.07.05.498863
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
S. Frank
中科院分区：
文献类型：
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作者：
S. Frank
转录因子（TF）影响mRNA的表达。从本质上讲，TF形成了一个控制细胞功能许多方面的大型计算网络。本文介绍了一种优化TF网络的计算方法。该方法扩展了人工神经网络优化的最新进展。在一个简单的例子中，计算优化发现了一个四维TF网络，该网络在许多天内保持昼夜节律，成功地缓冲了分子动力学中的强随机扰动，并夹带到外部昼夜信号，该信号以几天的间隔随机打开和关闭。这项工作突出了理解计算TF和神经网络如何获得信息和提高性能，以及大型TF网络如何获得遗传变异和疾病趋势的类似挑战。
Transcription factors (TFs) affect the expression of mRNAs. In essence, the TFs form a large computation network that controls many aspects of cellular function. This article introduces a computational method to optimize TF networks. The method extends recent advances in artificial neural network optimization. In a simple example, computational optimization discovers a four-dimensional TF network that maintains a circadian rhythm over many days, successfully buffering strong stochastic perturbations in molecular dynamics and entraining to an external day-night signal that randomly turns on and off at intervals of several days. This work highlights the similar challenges in understanding how computational TF and neural networks gain information and improve performance, and in how large TF networks may acquire a tendency for genetic variation and disease.