Predicting Protein Complexes in Weighted Dynamic PPI Networks Based on ICSC

Joint Authors

Lei, Xiujuan
Zhao, Jie
Wu, Fang-Xiang

Source

Complexity

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

Philosophy

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