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Quantitative Biology

, Volume 6, Issue 4, pp 313–320 | Cite as

On the statistical significance of protein complex

  • Youfu Su
  • Can Zhao
  • Zheng Chen
  • Bo Tian
  • Zengyou He
Research Article
  • 26 Downloads

Abstract

Background

Statistical validation of predicted complexes is a fundamental issue in proteomics and bioinformatics. The target is to measure the statistical significance of each predicted complex in terms of p-values. Surprisingly, this issue has not received much attention in the literature. To our knowledge, only a few research efforts have been made towards this direction.

Methods

In this article, we propose a novel method for calculating the p-value of a predicted complex. The null hypothesis is that there is no difference between the number of edges in target protein complex and that in the random null model. In addition, we assume that a true protein complex must be a connected subgraph. Based on this null hypothesis, we present an algorithm to compute the p-value of a given predicted complex.

Results

We test our method on five benchmark data sets to evaluate its effectiveness.

Conclusions

The experimental results show that our method is superior to the state-of-the-art algorithms on assessing the statistical significance of candidate protein complexes.

Keywords

predicted complex statistical significance testing subgraph mining community detection 

Notes

Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (No. 61572094), the Fundamental Research Funds for the Central Universities of China (Nos. DUT2017TB02 and DUT14QY07). Additionally, we want to thank the academic support received from Mr. Ben Teng and Dr. Xiuli Ma.

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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Youfu Su
    • 1
  • Can Zhao
    • 1
  • Zheng Chen
    • 1
  • Bo Tian
    • 1
  • Zengyou He
    • 1
    • 2
  1. 1.School of SoftwareDalian University of TechnologyDalianChina
  2. 2.Key Laboratory for Ubiquitous Network and Service Software of LiaoningDalianChina

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