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无细胞系统的计算生物学

Mansi Acharya¹, Indra Mani²

¹School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India.

Progress in molecular biology and translational science

|January 25, 2026

概括

无细胞系统 (CFS) 为生物应用提供了一个模块化平台. 本综述探讨了优化CFS设计的计算方法,整合机械学和机器学习方法以提高速度和清晰度.

科学领域:

合成生物学合成生物学
计算生物学是一种计算生物学.
生物技术是生物技术.

背景情况:

无细胞系统 (CFS) 将生物过程与活细胞分离.
CFS提供了一个快速的模块化平台,用于生物传感,路径原型和蛋白质生产.
计算建模对于CFS设计和优化至关重要.

研究的目的:

审查CFS设计和优化的机械和数据驱动的计算方法.
为了比较转录-翻译动态和代谢途径的不同建模框架.
评估机器学习策略用于CFS中的序列到函数映射.

主要方法:

普通微分方程 (ODE) 和转录-翻译动态的随机模拟的比较.
基因组规模代谢模型 (GEMs) 和流量平衡分析 (FBA) 对无细胞提取物的调整.
机器学习 (ML) 的评估,用于使用高通量无细胞测试进行序列到功能映射.

主要成果:

用于CFS建模和设计的软件工具的概述.
讨论CFS在诊断,代谢途径重建和蛋白质合成中的应用.
突出了基于CRISPR的调控在无细胞环境中的多层遗传电路的进展.

结论:

确定的差距包括测试标准化,公共数据集和混合建模.
提出了社区资源和混合建模努力的路线图.
强调将机械清晰度与ML驱动的速度结合起来,以实现未来的CFS开发.

关键词:

克里斯普尔是什么意思?克里斯普尔是什么意思?无细胞系统是无细胞系统.计算建模计算建模基因组规模模型机器学习机器学习合成生物学合成生物学

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