Departamento de Nutrición y Bioquímica, Facultad de Ciencias, Pontificia Universidad Javeriana, Edf. Carlos Ortiz, Oficina 107, Cra. 7 40-62, Bogotá 110231, Colombia.
Laboratorio de Bioinformática y Biología de Sistemas, Universidad Nacional de Colombia, Bogotá 111321, Colombia.
Int J Mol Sci. 2023 Dec 27;25(1):365. doi: 10.3390/ijms25010365.
Control theory, a well-established discipline in engineering and mathematics, has found novel applications in systems biology. This interdisciplinary approach leverages the principles of feedback control and regulation to gain insights into the complex dynamics of cellular and molecular networks underlying chronic diseases, including neurodegeneration. By modeling and analyzing these intricate systems, control theory provides a framework to understand the pathophysiology and identify potential therapeutic targets. Therefore, this review examines the most widely used control methods in conjunction with genomic-scale metabolic models in the steady state of the multi-omics type. According to our research, this approach involves integrating experimental data, mathematical modeling, and computational analyses to simulate and control complex biological systems. In this review, we find that the most significant application of this methodology is associated with cancer, leaving a lack of knowledge in neurodegenerative models. However, this methodology, mainly associated with the Minimal Dominant Set (MDS), has provided a starting point for identifying therapeutic targets for drug development and personalized treatment strategies, paving the way for more effective therapies.
控制理论是工程学和数学中一门成熟的学科,它在系统生物学中找到了新的应用。这种跨学科的方法利用反馈控制和调节的原理,深入了解慢性疾病(包括神经退行性疾病)的细胞和分子网络的复杂动态。通过对这些复杂系统进行建模和分析,控制理论为理解病理生理学和确定潜在的治疗靶点提供了一个框架。因此,本综述检查了最广泛使用的控制方法,以及在多组学类型的稳态下与基因组规模代谢模型的结合。根据我们的研究,这种方法涉及整合实验数据、数学建模和计算分析,以模拟和控制复杂的生物系统。在本综述中,我们发现这种方法的最重要应用与癌症有关,而在神经退行性模型中则缺乏相关知识。然而,这种主要与最小支配集(MDS)相关的方法为药物开发和个性化治疗策略的治疗靶点的识别提供了一个起点,为更有效的治疗方法铺平了道路。