代谢建模:了解植物代谢的机房
Tiago M Machado1, Nadine Töpfer1, Fatemeh Soltani1
1Institute for Plant Sciences, Cluster of Excellence on Plant Sciences (CEPLAS), University of Cologne, Zülpicher Straße 47b, 50674, Cologne, Germany.
Journal of plant physiology
|September 16, 2025
概括
使用网络方法研究植物新陈代谢提供了整体的见解. 本综述涵盖了植物代谢建模的最新趋势,包括机器学习和混合战略,用于更广泛的应用.
科学领域:
- 植物生物学 植物生物学
- 代谢网络是代谢网络.
- 计算生物学 计算生物学
背景情况:
- 植物的生长和发育依赖于在代谢网络中组织的复杂生化反应.
- 了解这些相互连接的网络对于对植物代谢的机械洞察至关重要.
- 网络视角和in silico建模为研究植物代谢提供了一个整体的方法.
研究的目的:
- 审查植物代谢建模的最新进展.
- 突出植物科学中代谢模型的扩展范围和应用.
- 讨论新兴的计算工具和未来的研究方向.
主要方法:
- 巩固植物代谢建模文献中最近的趋势.
- 讨论从亚细胞到生态系统尺度的网络层面的方法.
- 对机器学习,深度学习和混合策略进行模型增强的审查.
主要成果:
- 植物代谢建模现在包括各种物种,基因型和专门的途径.
- 模型越来越多地捕捉到时空动态和植物微生物相互作用.
- 机器学习和混合方法正在改善模型重建和分析.
结论:
- 植物代谢建模是理解复杂生物过程的强大工具.
- 该领域正在迅速发展,有新的计算方法和更广泛的应用.
- 未来的研究应该集中在整合多样化的数据和解决当前的挑战.
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