从双向时间序列状态传输网络的不规则观测中学习代谢动态.
Shaohua Xu1,2, Ting Xu1, Yuping Yang1
1School of Basic Medical Sciences and the First Affiliated Hospital Department of Radiation Oncology, Zhejiang University School of Medicine, Hangzhou, China.
mSystems
|July 26, 2024
概括
我们开发了一种新的网络模型,即双向时间序列状态传输网络 (BTSTN),以从不规则的生物数据中准确地建模微生物代谢动态,提高生物制造效率.
科学领域:
- 生物技术是生物技术.
- 系统生物学 系统生物学
- 机器学习 机器学习
背景情况:
- 模拟微生物代谢动态对于优化生物制造工艺至关重要.
- 传统的白盒模型与缺乏详细网络信息的工业菌株作斗争.
- 现有的黑子模型通常需要对不规则的时间序列数据进行预处理,从而引入错误.
研究的目的:
- 引入一种新的深度学习方法,直接从不规则的时间序列观测中建模代谢动态.
- 解决现有方法在处理现实世界生物制造数据方面的局限性,这些数据往往是杂和不完整的.
- 提高用于工业应用的代谢动态建模的准确性和稳定性.
主要方法:
- 开发双向时间序列状态传输网络 (BTSTN),一个深度学习架构.
- 培训和评估使用来自理想动态系统的合成数据集.
- 用现实世界发酵过程数据集进行验证,显示不规则的测量和噪声.
主要成果:
- BTSTN准确地重建了微生物代谢系统的动态行为.
- 该模型证明了对未来代谢轨迹的可靠预测.
- 在处理缺失测量和噪声方面,BTSTN的性能超过了最先进的方法.
结论:
- BTSTN提供了一个强大的新工具,用于建模微生物代谢动态,特别是从具有挑战性的,不规则的数据.
- 这种方法提高了生物制造过程优化的可靠性和准确性.
- 由于BTSTN能够从不规则的数据中原生学习,这使得它在该领域取得了重大进展.
相关概念视频
01:27State Space Representation
190
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
Consider an RLC circuit, a...
190
01:21State Space to Transfer Function
191
The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
191
01:23Transfer Function to State Space
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State-space representation is a powerful tool for simulating physical systems on digital computers, necessitating the conversion of the transfer function into state-space form. Consider an nth-order linear differential equation with constant coefficients, like those encountered in an RLC circuit. The state variables are selected as the output and its n−1 derivatives. Differentiating these variables and substituting them back into the original equation produces the state equations.
In an...
In an...
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