Predicting Protein Complexes in Weighted Dynamic PPI Networks Based on ICSC
Joint Authors
Lei, Xiujuan
Zhao, Jie
Wu, Fang-Xiang
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-08-28
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Protein complexes play a critical role in understanding the biological processes and the functions of cellular mechanisms.
Most existing protein complex detection algorithms cannot reflect dynamics of protein complexes.
In this paper, a novel algorithm named Improved Cuckoo Search Clustering (ICSC) algorithm is proposed to detect protein complexes in weighted dynamic protein-protein interaction (PPI) networks.
First, we constructed weighted dynamic PPI networks and detected protein complex cores in each dynamic subnetwork.
Then, ICSC algorithm was used to cluster the protein attachments to the cores.
The experimental results on both DIP dataset and Krogan dataset demonstrated that ICSC algorithm is more effective in identifying protein complexes than other competing methods.
American Psychological Association (APA)
Zhao, Jie& Lei, Xiujuan& Wu, Fang-Xiang. 2017. Predicting Protein Complexes in Weighted Dynamic PPI Networks Based on ICSC. Complexity،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1142825
Modern Language Association (MLA)
Zhao, Jie…[et al.]. Predicting Protein Complexes in Weighted Dynamic PPI Networks Based on ICSC. Complexity No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1142825
American Medical Association (AMA)
Zhao, Jie& Lei, Xiujuan& Wu, Fang-Xiang. Predicting Protein Complexes in Weighted Dynamic PPI Networks Based on ICSC. Complexity. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1142825
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142825