基于约束的建模中枢性优化:对人类新陈代谢的应用
Ronan M T Fleming1,2,3, Hulda S Haraldsdottir2, Le Hoai Minh2
1Metabolomics and Analytics Center, Leiden Academic Centre for Drug Research, Leiden University, Wassenaarseweg 76, Leiden 2333 CC, The Netherlands.
Bioinformatics (Oxford, England)
|September 12, 2023
概括
我们开发了新的算法来解决基于约束的建模中复杂的核心优化问题. 我们的方法有效地找到生物化学网络分析的近似解决方案,改进现有方法.
科学领域:
- 计算生物学 计算生物学
- 优化优化 优化优化
- 系统生物学 系统生物学
背景情况:
- 核心优化问题在基于约束的建模中对于如一致性测试和稀疏解决方案计算等任务至关重要.
- 对于这些计算复杂问题的现有方法往往缺乏在多项式时间内准确和全球最佳的解决方案.
研究的目的:
- 在基于约束的建模中,将枢能数优化问题重新阐述为凸函数的差异.
- 开发和测试新的算法,以大致解决这些重构的问题.
主要方法:
- 通过非凸连续函数对零规范进行近似,以转换枢纽性优化问题.
- 采用一系列凸的程序来代地解决重构的问题.
- 将算法应用于生物化学网络,包括人类代谢重建.
主要成果:
- 实施了新的算法并进行了数值测试,证明了效率和实际实用性.
- 开发的算法与基于约束的建模中对枢性优化的现有相关方法匹配或优于现有的相关方法.
- 成功地从人类代谢重建中提取热力学流量平衡分析模型的应用.
结论:
- 拟议的方法提供了一种有效的方法来解决基于约束的建模中具有挑战性的枢密度优化问题.
- 这些算法为分析生化网络和提取相关模型提供了实用和高效的解决方案.
- 开源实现可用于可重现性和集成到现有的建模工作流.
相关概念视频
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