从实验方法到计算技术:蛋白质-蛋白质相互作用预测综述

Fiona Browne, Huiru Zheng, Haiying Wang, F. Azuaje
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引用次数: 36

摘要

了解生物体细胞系统特性的关键一步是在蛋白质组学范围内完整且尽可能准确地绘制蛋白质-蛋白质相互作用(PPIs)网络。揭示蛋白质的多种功能及其在细胞内的相互作用可以提高我们对疾病的理解,并为开发新的治疗方法提供基础。大规模高通量实验的发展导致了大量数据的产生,这些数据有助于发现ppi。然而,这些数据往往是错误的,并且在相互作用组的覆盖范围中受到限制。因此,需要额外的实验和计算方法来加速PPIs的发现。本文回顾了PPI的预测,指出了关键的预测原则,并强调了目前用于推断PPI网络的常用实验和计算技术以及该领域的相关研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From Experimental Approaches to Computational Techniques: A Review on the Prediction of Protein-Protein Interactions
A crucial step towards understanding the properties of cellular systems in organisms is to map their network of protein-protein interactions (PPIs) on a proteomic-wide scale completely and as accurately as possible. Uncovering the diverse function of proteins and their interactions within the cell may improve our understanding of disease and provide a basis for the development of novel therapeutic approaches. The development of large-scale high-throughput experiments has resulted in the production of a large volume of data which has aided in the uncovering of PPIs. However, these data are often erroneous and limited in interactome coverage. Therefore, additional experimental and computational methods are required to accelerate the discovery of PPIs. This paper provides a review on the prediction of PPIs addressing key prediction principles and highlighting the common experimental and computational techniques currently employed to infer PPI networks along with relevant studies in the area.
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