代谢目标和权衡:推断和应用
Da-Wei Lin1,2, Saanjh Khattar3, Sriram Chandrasekaran1,3,4,5
1Center for Bioinformatics and Computational Medicine, Ann Arbor, MI 48109, USA.
Metabolites
|February 25, 2025
概括
了解细胞目标是生物网络建模的关键. 新的方法整合了多omics数据,揭示了细胞如何平衡资源使用的不同功能,而不仅仅是增长.
科学领域:
- 系统生物学 系统生物学
- 代谢工程是代谢工程.
- 计算生物学 计算生物学
背景情况:
- 细胞目标对于模拟生物网络在代谢工程和药物发现等领域至关重要.
- 细胞在环境约束下管理资源以实现生物目标,其目标超越生物质生产,扩展到组织功能和平衡.
- 哺乳动物细胞表现出不同的代谢目标,包括支持组织功能,发育和氧化还原平衡,而不仅仅是生长.
研究的目的:
- 审查从多omics数据确定细胞代谢目标和权衡的方法.
- 将基因表达模式与代谢表型相结合,以便全面了解细胞行为.
- 探索将蜂目标集成到先进应用中.
主要方法:
- 利用单细胞欧米克技术的进步.
- 使用复杂的代谢建模技术.
- 利用机器学习和深度学习算法进行客观推断.
主要成果:
- 现在可以在转录组和代谢水平上推断细胞目标.
- 将基因表达与代谢表型的整合提供了更深入的生物学见解.
- 形模型为细胞适应和反应提供预测能力.
结论:
- 在模型揭示了细胞适应环境变化,药物治疗和基因修改的机制.
- 将细胞目标纳入模型具有针对个性化医学和药物发现的巨大潜力.
- 这种方法推进了系统生物学,组织工程和治疗开发.
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