OMMR:一种关键模块重叠部分评价指标

Zhang Xiao-xia; Xiao Qiang-hua; Li Bin; Hu Sai; Xiong Hui-jun; Zhao Bi-hai

doi:10.1631/FITEE.1400282

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OMMR:一种关键模块重叠部分评价指标

计算机与自动化 | Updated：2022-06-14

- OMMR:一种关键模块重叠部分评价指标
- Overlap maximum matching ratio (OMMR): a new measure to evaluate overlaps of essential modules*
- 信息与电子工程前沿（英文） 2015年16卷第4期页码：293-300
- 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：
  
  *Project supported by the National Scientific Research Foundation of Hunan Province, China (Nos. 14C0096, 10C0408, and 10B010), the Natural Science Foundation of Hunan Province, China (Nos. 13JJ4106 and 14JJ3138), and the Science and Technology Plan Project of Hunan Province, China (No. 2010FJ3044)
- DOI：10.1631/FITEE.1400282
  中图分类号：
- 收稿：2014-08-06，
  
  修回：2015-03-09，
  
  录用：2014-12-16，
  
  纸质出版：2015-04
- Accepted：
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OMMR:一种关键模块重叠部分评价指标[J]. 信息与电子工程前沿（英文）, 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.
OMMR:一种关键模块重叠部分评价指标[J]. 信息与电子工程前沿（英文）, 2015,16(4):293-300. DOI： 10.1631/FITEE.1400282.

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

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。

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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