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将时间延迟纳入大型生物调控网络动态建模的过程命中框架。

Incorporating Time Delays in Process Hitting Framework for Dynamical Modeling of Large Biological Regulatory Networks.

作者信息

Sheikh Iftikhar Ali, Ahmad Jamil, Magnin Morgan, Roux Olivier

机构信息

Research Centre for Modeling and Simulation, National University of Sciences and Technology, Islamabad, Pakistan.

Department of Computer Science and Information Technology, University of Malakand, Chakdara, Pakistan.

出版信息

Front Physiol. 2019 Feb 15;10:90. doi: 10.3389/fphys.2019.00090. eCollection 2019.

Abstract

Modeling and simulation of molecular systems helps in understanding the behavioral mechanism of biological regulation. Time delays in production and degradation of expressions are important parameters in biological regulation. Constraints on time delays provide insight into the dynamical behavior of a Biological Regulatory Network (BRN). A recently introduced Process Hitting (PH) Framework has been found efficient in static analysis of large BRNs, however, it lacks the inference of time delays and thus determination of their constraints associated with the evolution of the expression levels of biological entities of BRN is not possible. In this paper we propose a scheme for introducing time delays in Process Hitting Framework for dynamical modeling and analysis of Large Biological Regulatory Networks. It provides valuable insights into the time delays corresponding to the changes in the expression levels of biological entities thus possibly helping in identification of therapeutic targets. The proposed framework is applied to a well-known BRNs of λ and ERBB Receptor-regulated G1/S transition involved in the breast cancer to demonstrate the viability of our approach. Using the proposed approach, we are able to perform goal-oriented reduction of the BRN and also determine the constraints on time delays characterizing the evolution (dynamics) of the reduced BRN.

摘要

分子系统的建模与仿真有助于理解生物调节的行为机制。表达产物生成和降解过程中的时间延迟是生物调节中的重要参数。时间延迟的限制为生物调节网络(BRN)的动态行为提供了深入了解。最近引入的过程命中(PH)框架在大型BRN的静态分析中已被证明是有效的,然而,它缺乏对时间延迟的推断,因此无法确定与BRN生物实体表达水平演变相关的时间延迟限制。在本文中,我们提出了一种在过程命中框架中引入时间延迟的方案,用于大型生物调节网络的动态建模和分析。它为与生物实体表达水平变化相对应的时间延迟提供了有价值的见解,从而可能有助于确定治疗靶点。所提出的框架应用于乳腺癌中涉及的λ和ERBB受体调节的G1/S转换这一著名的BRN,以证明我们方法的可行性。使用所提出的方法,我们能够对BRN进行面向目标的简化,并确定表征简化后的BRN演变(动态)的时间延迟限制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a007/6385622/f665cd7d0c86/fphys-10-00090-g0001.jpg

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