多关系蛋白质网络构建及其应用研究

胡赛; 熊慧军; 李学勇; 赵碧海; 倪问尹; 杨品红; 刘臻

doi:10.16383/j.aas.2015.c150187

多关系蛋白质网络构建及其应用研究

doi: 10.16383/j.aas.2015.c150187

1.
长沙学院数学与计算机科学系长沙 410022;
2.
湖南文理学院生命科学学院常德 415000;
3.
长沙学院生物与环境工程系长沙 410022

基金项目:

国家自然科学基金(11501054),湖南省自然科学基金(13JJ4106,14JJ3138),湖南省教育厅项目(10C0408,15C0124),湖南省科技计划项目(2010FJ3044,2015GK3072),水产高效健康生产湖南省协同创新中心资助

详细信息

作者简介:
胡赛长沙学院数学与计算机科学系副教授. 2003 年获得湖南大学数学与计量经济学院硕士学位. 主要研究方向为数理统计. E-mail: husaiccsu@163.com

通讯作者:
赵碧海博士, 长沙学院数学与计算机科学系副教授.2014 年获得中南大学信息学院博士学位.主要研究方向为生物信息学, 数据挖掘.本文通信作者.

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- 被引次数: 0
出版历程
- 收稿日期: 2015-04-10
- 修回日期: 2015-09-23
- 刊出日期: 2015-12-20

Construction of Multi-relation Protein Networks and Its Application

1.
Department of Mathematics and Computer Science, Changsha University, Changsha 410022;
2.
School of Life Science, Hunan University of Arts and Science, Changde 415000;
3.
Department of Biological and Environmental Engineering, Changsha University, Changsha 410022

Funds:

Supported by National Natural Science Foundation of China (11501054), Natural Science Foundation of Hunan Province (13JJ4106, 14JJ3138), National Scientific Research Foundation of Hunan Province (10C0408, 15C0124), Science and Technology Plan Project of Hunan Province (2010FJ3044, 2015GK3072), and Collaborative Innovation Center for Efficient and Health Production of Fisheries in Hunan Province

摘要

摘要: 考虑到不同类型的相互作用对于功能预测的作用各不相同, 结合蛋白质相互作用网络和蛋白质结构域信息构建多关系蛋白质网络, 并为每种类型的相互作用赋予不同的遍历优先级.基于多关系网络, 提出一种蛋白质功能预测方法FPM (Functions prediction based on multi-relational networks).对于未注释的蛋白质, 算法遍历与该蛋白质相连的, 具有最高优先级的所有相互作用, 形成一个候选邻居节点集合.最后根据邻居节点集合形成预测的功能集合, 并为每一项功能评分、排序.与其他算法对比结果表明, FPM方法的性能优于其他的功能预测方法.
- 多关系网络 /
- 蛋白质功能 /
- 蛋白质相互作用 /
- 优先级 /
- 结构域
Abstract: Considering the different influences of different types of interactions in protein function prediction, we construct a multi-relation interaction network by integrating protein-protein interaction (PPI) network and proteins' domain information and provide different priorities for different types of interactions. We propose a protein function prediction method, named functions prediction based on multi-relation networks (FPM) to infer protein functions. Given an unannotated protein, all interactions with highest priority associated with the protein are visited to form a candidate neighbor nodes set. Finally, we sort all functions of the neighbor nodes and select part of them to predict an unknown protein. Comparson with other methods show that our method outperforms other function prediction methods.
- Multi-relation network /
- protein functions /
- protein-protein interaction (PPI) /
- priority /
- domain

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参考文献(20)

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