基于静态网络的蛋白质复合物预测方法综述
A Survey of Computational Methods for Protein Complexes Prediction Based on Static PPI Networks
DOI: 10.12677/SEA.2018.73018, PDF,  被引量    科研立项经费支持
作者: 于杨：沈阳师范大学，软件学院，辽宁 沈阳
关键词: 蛋白质网络；聚类；复合物预测；计算方法；Protein-Protein Interaction Network； Clustering； Complex Prediction； Computational Methods
摘要: 蛋白质复合物通过相互作用蛋白质形成，表现出多样的生物功能。使用计算方法从生物网络中预测蛋白质复合物不仅对于理解生物活动的机制和疾病的发病机理具有重要意义，而且可以弥补生物高通量实验方法的不足。本文介绍分析两类基于静态网络蛋白质复合物预测的方法，讨论蛋白质复合物预测算法的不足，进一步分析探讨蛋白质复合物预测所面临的挑战。
Abstract: Protein complexes are formed by interacting proteins and exhibit diverse biological functions. Protein complexes are predicted by computational methods from biological networks, which is not only important for understanding the mechanisms of biological activities and the pathogenesis of diseases, but also for making up the deficiencies of biological high-throughput experimental methods. In this paper, two types of prediction methods based on static network protein complexes are introduced and analyzed. Secondly, we discuss the deficiencies of protein complex algorithms and the challenges of this field.
文章引用：于杨. 基于静态网络的蛋白质复合物预测方法综述[J]. 软件工程与应用, 2018, 7(3): 151-159. https://doi.org/10.12677/SEA.2018.73018

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