Application of Improved K-mean Clustering in Predicting Protein-Protein Interactions

With the increasing availability of complete genome sequences, there are more excellent opportunity for further research and development of tools for functional studies in proteomics. Phylogenetic profile is a basic non-homology method in functional proteomics. This paper describes the theory of phy...

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Bibliographic Details
Main Authors: Pingping Sun, Yanan Ma, Yazhuo Wei, Zhiqiang Ma, Linying Lu, Ying Cui, Ping Huang
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Bioinformatics
Clustering algorithms
Evolution (biology)
Genomics
improved K-mean clustering
Iterative algorithms
Organisms
phylogenetic profile
Phylogeny
protein-protein interactions
Proteins
Proteomics
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Summary:With the increasing availability of complete genome sequences, there are more excellent opportunity for further research and development of tools for functional studies in proteomics. Phylogenetic profile is a basic non-homology method in functional proteomics. This paper describes the theory of phylogenetic profile, focuses on the improvement of K-mean clustering algorithm in analyzing the protein phylogenetic profile; also compare the method with the traditional K-mean clustering algorithm. The experimental results show that the improved K-mean clustering algorithm is fast and effective; it can quickly converge to the approximate optimal solution.
ISSN:1948-2914
1948-2922
DOI:10.1109/BMEI.2008.82