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Overlap maximum matching ratio (OMMR): a new measure to evaluate overlaps of essential modules*
- OMMR:一种关键模块重叠部分评价指标
- Frontiers of Information Technology & Electronic Engineering Vol. 16, Issue 4, Pages: 293-300(2015)
- Affiliations：
1.Department of Mathematics and Computer Science, Changsha University, Changsha 410003, China
2.School of Information Science and Engineering, Central South University, Changsha 410083, China
- Author bio：
†E-mail:zhangxx111@yeah.netbihaizhao@163.com
‡Corresponding Author
- Funds：
DOI：10.1631/FITEE.1400282
CLC：Received：06 August 2014，
Revised：2015-03-09，
Accepted：16 December 2014，
Published：2015-04
- Accepted：
Scan QR Code
Zhang Xiao-xia, Xiao Qiang-hua, Li Bin, et al. 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.
Zhang Xiao-xia, Xiao Qiang-hua, Li Bin, et al. 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. DOI： 10.1631/FITEE.1400282.
摘要
目的
2
设计蛋白质复合物或功能模块重叠部分评价指标。
创新点
2
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
2
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
2
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。
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.
关键词
Keywords
references
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