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CLC number: TP311; R857.3

On-line Access: 2015-04-03

Received: 2014-08-06

Revision Accepted: 2014-12-16

Crosschecked: 2015-03-09

Cited: 3

Clicked: 3922

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Bi-hai Zhao

http://orcid.org/0000-0003-0870-7468

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Frontiers of Information Technology & Electronic Engineering  2015 Vol.16 No.4 P.293-300

http://doi.org/10.1631/FITEE.1400282


Overlap maximum matching ratio (OMMR): a new measure to evaluate overlaps of essential modules


Author(s):  Xiao-xia Zhang, Qiang-hua Xiao, Bin Li, Sai Hu, Hui-jun Xiong, Bi-hai Zhao

Affiliation(s):  Department of Mathematics and Computer Science, Changsha University, Changsha 410003, China; more

Corresponding email(s):   zhangxx111@yeah.net, bihaizhao@163.com

Key Words:  Protein-protein interaction network, Essential protein modules, Overlap, Overlap maximum matching ratio


Xiao-xia Zhang, Qiang-hua Xiao, Bin Li, Sai Hu, Hui-jun Xiong, Bi-hai Zhao. Overlap maximum matching ratio (OMMR): a new measure to evaluate overlaps of essential modules[J]. Frontiers of Information Technology & Electronic Engineering, 2015, 16(4): 293-300.

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author="Xiao-xia Zhang, Qiang-hua Xiao, Bin Li, Sai Hu, Hui-jun Xiong, Bi-hai Zhao",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="16",
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pages="293-300",
year="2015",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1400282"
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%A Qiang-hua Xiao
%A Bin Li
%A Sai Hu
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A1 - Xiao-xia Zhang
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A1 - Bin Li
A1 - Sai Hu
A1 - Hui-jun Xiong
A1 - Bi-hai Zhao
J0 - Frontiers of Information Technology & Electronic Engineering
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DOI - 10.1631/FITEE.1400282


Abstract: 
Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell’s mechanism. The development of the yeast two-hybrid, tandem affinity purification, and mass spectrometry high-throughput proteomic techniques supplies a large amount of protein-protein interaction data, which make it possible to predict overlapping complexes through computational methods. Research shows that overlapping complexes can contribute to identifying essential proteins, which are necessary for the organism to survive and reproduce, and for life’s activities. Scholars pay more attention to the evaluation of protein complexes. However, few of them focus on predicted overlaps. In this paper, an evaluation criterion called overlap maximum matching ratio (OMMR) is proposed to analyze the similarity between the identified overlaps and the benchmark overlap modules. Comparison of essential proteins and gene ontology (GO) analysis are also used to assess the quality of overlaps. We perform a comprehensive comparison of serveral overlapping complexes prediction approaches, using three yeast protein-protein interaction (PPI) networks. We focus on the analysis of overlaps identified by these algorithms. Experimental results indicate the important of overlaps and reveal the relationship between overlaps and identification of essential proteins.

In this paper, authors propose a new measure, namely OMMR, to evaluate the quality of overlaps of protein complexes identified. In general, unlike previous works that only focus on the overlapping between two protein complexes, this new measure targets to compute the overall overlapping score for all protein complexes identified.

OMMR:一种关键模块重叠部分评价指标

目的:设计蛋白质复合物或功能模块重叠部分评价指标。
创新点:考虑到蛋白质复合物重叠部分与关键蛋白质识别之间存在紧密联系,首次提出关键模块评价指标—重叠最大匹配率(OMMR),可用于评价挖掘的具有重叠部分的功能模块算法优劣,从而进一步服务于关键蛋白质的识别。
方法:首先,通过Benchmark集分析,得到参考Overlap集合。然后得到功能模块预测算法得到的复合物集合的overlap集合,利用公式(5)得到该预测算法的OMMR值。
结论:重叠蛋白复合物,尤其是它们的重叠部分,在识别必要性蛋白中发挥重要作用。本文提出名为OMMR的方法来评估必要性模块的重叠部分。实验结果表明重叠部分的重要性,并揭示重叠部分与关键性蛋白识别之间关系。

关键词:蛋白质相互作用网络;关键模块;重叠部分;OMMR

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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