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Semi-Markov Model of a Swarm Functioning Read chapter Read first chapter

2018 | OriginalPaper | Chapter

ACO Based Core-Attachment Method to Detect Protein Complexes in Dynamic PPI Networks

Authors : Jing Liang, Xiujuan Lei, Ling Guo, Ying Tan

Published in: Advances in Swarm Intelligence

Publisher: Springer International Publishing

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Abstract

Proteins complexes accomplish biological functions such as transcription of DNA and translation of mRNA. Detecting protein complexes correctly and efficiently is becoming a challenging task. This paper presents a novel algorithm, core-attachment based on ant colony optimization (CA-ACO), which detects complexes in three stages. Firstly, initialize the similarity matrix. Secondly, complexes are predicted by clustering in the dynamic PPI networks. In the step, the clustering coefficient of every node is also computed. A node whose clustering coefficient is greater than the threshold is added to the core protein set. Then we mark every neighbor node of core proteins with unique core label during picking and dropping. Thirdly, filtering processes are carried out to obtain the final complex set. Experimental results show that CA-ACO algorithm had great superiority in precision, recall and f-measure compared with the state-of-the-art methods such as ClusterONE, DPClus, MCODE and so on.

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Metadata
Title
ACO Based Core-Attachment Method to Detect Protein Complexes in Dynamic PPI Networks
Authors
Jing Liang
Xiujuan Lei
Ling Guo
Ying Tan
Copyright Year
2018
Book
Advances in Swarm Intelligence

Print ISBN: 978-3-319-93814-1

Electronic ISBN: 978-3-319-93815-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-93815-8_11

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