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使用定理证明对系统生物学进行形式推理。

Formal reasoning about systems biology using theorem proving.

作者信息

Rashid Adnan, Hasan Osman, Siddique Umair, Tahar Sofiène

机构信息

School of Electrical Engineering and Computer Science, National University of Sciences and Technology, Islamabad, Pakistan.

Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada.

出版信息

PLoS One. 2017 Jul 3;12(7):e0180179. doi: 10.1371/journal.pone.0180179. eCollection 2017.

Abstract

System biology provides the basis to understand the behavioral properties of complex biological organisms at different levels of abstraction. Traditionally, analysing systems biology based models of various diseases have been carried out by paper-and-pencil based proofs and simulations. However, these methods cannot provide an accurate analysis, which is a serious drawback for the safety-critical domain of human medicine. In order to overcome these limitations, we propose a framework to formally analyze biological networks and pathways. In particular, we formalize the notion of reaction kinetics in higher-order logic and formally verify some of the commonly used reaction based models of biological networks using the HOL Light theorem prover. Furthermore, we have ported our earlier formalization of Zsyntax, i.e., a deductive language for reasoning about biological networks and pathways, from HOL4 to the HOL Light theorem prover to make it compatible with the above-mentioned formalization of reaction kinetics. To illustrate the usefulness of the proposed framework, we present the formal analysis of three case studies, i.e., the pathway leading to TP53 Phosphorylation, the pathway leading to the death of cancer stem cells and the tumor growth based on cancer stem cells, which is used for the prognosis and future drug designs to treat cancer patients.

摘要

系统生物学为理解复杂生物有机体在不同抽象层次上的行为特性提供了基础。传统上,对基于系统生物学的各种疾病模型的分析是通过纸笔证明和模拟来进行的。然而,这些方法无法提供准确的分析,这对于人类医学的安全关键领域来说是一个严重的缺陷。为了克服这些限制,我们提出了一个框架来对生物网络和途径进行形式化分析。具体而言,我们在高阶逻辑中形式化反应动力学的概念,并使用HOL Light定理证明器对一些常用的基于反应的生物网络模型进行形式化验证。此外,我们已将我们早期对Zsyntax(即一种用于推理生物网络和途径的演绎语言)的形式化从HOL4移植到HOL Light定理证明器,使其与上述反应动力学的形式化兼容。为了说明所提出框架的有用性,我们给出了三个案例研究的形式化分析,即导致TP53磷酸化的途径、导致癌症干细胞死亡的途径以及基于癌症干细胞的肿瘤生长,这些用于癌症患者的预后和未来药物设计。

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