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Essential Proteins Discovery from Weighted Protein Interaction Networks

机译：从加权蛋白质相互作用网络发现必需蛋白质

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摘要

Identifying essential proteins is important for understanding the minimal requirements for cellular survival and development. Fast growth in the amount of available protein-protein interactions has produced unprecedented opportunities for detecting protein essentiality on network level. A series of centrality measures have been proposed to discover essential proteins based on network topology. However, most of them treat all interactions equally and are sensitive to false positives. In this paper, six standard centrality measures are redefined to be used in weighted network. A new method for weighing protein-protein interactions is proposed based on the combination of logistic regression-based model and function similarity. The experimental results on yeast network show that the weighting method can improve the performance of centrality measures considerably. More essential proteins are discovered by the weighted centrality measures than by the original centrality measures used in unweighted network. Even about 20% improvements are obtained from closeness centrality and subgraph centrality.
机译：鉴定必需蛋白对于理解细胞存活和发育的最低要求很重要。可用蛋白质-蛋白质相互作用量的快速增长为检测网络一级的蛋白质必需性提供了前所未有的机会。已经提出了一系列的中心化措施来发现基于网络拓扑的必需蛋白质。但是，它们中的大多数会平等地对待所有交互，并且对误报敏感。在本文中，重新定义了六个标准集中度度量以用于加权网络。基于逻辑回归模型和功能相似性相结合，提出了一种权衡蛋白质-蛋白质相互作用的新方法。酵母网络上的实验结果表明，加权方法可以显着提高集中度测量的性能。通过加权中心度度量比在未加权网络中使用的原始中心度度量发现了更多的必需蛋白质。从紧密度中心和子图中心性甚至可以获得约20％的改进。

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  • 来源
  • 会议地点 Storrs CT(US);Storrs CT(US)
  • 作者

    Min Li; Jianxin Wang; Huan Wang; Yi Pan;

  • 作者单位

    School of Information Science and Engineering, Central South University, Changsha 410083, P.R. China;

    rnSchool of Information Science and Engineering, Central South University, Changsha 410083, P.R. China Department of Computer Science, Georgia State University, Atlanta, GA 30302-4110, USA;

    rnSchool of Information Science and Engineering, Central South University, Changsha 410083, P.R. China;

    rnDepartment of Computer Science, Georgia State University, Atlanta, GA 30302-4110, USA;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物工程学（生物技术）;
  • 关键词

    essential protein; protein interaction network; centrality.;

    机译：必需蛋白蛋白质相互作用网络；中心性。;

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