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基于网络的方法预测必需基因或蛋白质:综述。

Network-based methods for predicting essential genes or proteins: a survey.

机构信息

School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.

出版信息

Brief Bioinform. 2020 Mar 23;21(2):566-583. doi: 10.1093/bib/bbz017.

Abstract

Genes that are thought to be critical for the survival of organisms or cells are called essential genes. The prediction of essential genes and their products (essential proteins) is of great value in exploring the mechanism of complex diseases, the study of the minimal required genome for living cells and the development of new drug targets. As laboratory methods are often complicated, costly and time-consuming, a great many of computational methods have been proposed to identify essential genes/proteins from the perspective of the network level with the in-depth understanding of network biology and the rapid development of biotechnologies. Through analyzing the topological characteristics of essential genes/proteins in protein-protein interaction networks (PINs), integrating biological information and considering the dynamic features of PINs, network-based methods have been proved to be effective in the identification of essential genes/proteins. In this paper, we survey the advanced methods for network-based prediction of essential genes/proteins and present the challenges and directions for future research.

摘要

被认为对生物或细胞的生存至关重要的基因被称为必需基因。预测必需基因及其产物(必需蛋白)对于探索复杂疾病的机制、研究活细胞所需的最小基因组以及开发新的药物靶点具有重要价值。由于实验室方法通常复杂、昂贵且耗时,因此提出了许多计算方法,以便从网络层面深入了解网络生物学和生物技术的快速发展,从而识别必需基因/蛋白质。通过分析蛋白质-蛋白质相互作用网络 (PINs) 中必需基因/蛋白质的拓扑特征,整合生物信息并考虑 PINs 的动态特征,基于网络的方法已被证明在鉴定必需基因/蛋白质方面非常有效。在本文中,我们调查了基于网络的必需基因/蛋白质预测的先进方法,并提出了未来研究的挑战和方向。

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