Plaugher Daniel, Murrugarra David
Department of Toxicology and Cancer Biology, University of Kentucky.
Department of Mathematics, University of Kentuckya.
bioRxiv. 2023 Apr 18:2023.04.17.537158. doi: 10.1101/2023.04.17.537158.
Modeling cell signal transduction pathways via Boolean networks (BNs) has become an established method for analyzing intracellular communications over the last few decades. What’s more, BNs provide a course-grained approach, not only to understanding molecular communications, but also for targeting pathway components that alter the long-term outcomes of the system. This has come to be known as . In this review we study the interplay of various approaches for controlling gene regulatory networks such as: algebraic methods, control kernel, feedback vertex set, and stable motifs. The study will also include comparative discussion between the methods, using an established cancer model of T-Cell Large Granular Lymphocyte (T-LGL) Leukemia. Further, we explore possible options for making the control search more efficient using reduction and modularity. Finally, we will include challenges presented such as the complexity and the availability of software for implementing each of these control techniques.
在过去几十年里,通过布尔网络(BNs)对细胞信号转导通路进行建模已成为分析细胞内通讯的一种既定方法。此外,布尔网络提供了一种粗粒度方法,不仅用于理解分子通讯,还用于靶向改变系统长期结果的通路成分。这已被称为 。在本综述中,我们研究了控制基因调控网络的各种方法之间的相互作用,例如:代数方法、控制核、反馈顶点集和稳定基序。该研究还将包括使用已建立的T细胞大颗粒淋巴细胞(T-LGL)白血病癌症模型对这些方法进行比较讨论。此外,我们探索了使用约简和模块化使控制搜索更高效的可能选项。最后,我们将阐述所呈现的挑战,例如实现这些控制技术中每一种的软件的复杂性和可用性。