Earticle

초록

영어

Detecting protein complexes is an important way to discover the relationship between network topological structure and its functional features in protein-protein interaction (PPI) network. The spectral clustering method is a popular approach. However, how to select its optimal Laplacian matrix is still an open problem. Here, we analyzed the performances of three graph Laplacian matrices (unnormalized symmetric graph Laplacians,, normalized symmetric graph Laplacians and normalized random walk graph Laplacians, respectively) in yeast PPI network. The comparison shows that the performances of unnormalized and normalized symmetric graph Laplacian matrices are similar, and they are better than that of normalized random walk graph Laplacian matrix. It is helpful to choose proper graph Laplacian matrix for PPI networks’ analysis.

목차

Abstract
 1. Introduction
 2. Materials and Methods
  2.1. Experimental Data
  2.2. Spectral Clustering Method
  2.3. Evaluation Criteria
 3. Results and Discussion
  3.1. Parameter gap
  3.2. Analysis of the Performance of Three Matrices
 4. Conclusions
 Acknowledgements
 References

키워드

저자

• Dong Yun-yuan [ College of Computer, National University of Defense Technology ]
• Keith C.C. Chan [ Department of computing, Hong Kong Polytechnic University ]
• Liu Qi-jun [ College of Science, National University of Defense Technology ]
• Wang Zheng-hua [ College of Computer, National University of Defense Technology ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605