DocumentCode :
3124430
Title :
An Average-Degree Based Method for Protein Complexes Identification
Author :
Yu, Liang ; Gao, Lin ; Li, Kui
Author_Institution :
Sch. of Comput. Sci. & Technol., Xidian Univ., Xi´´an, China
fYear :
2010
fDate :
18-20 June 2010
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, we propose an average-degree based cluster mining algorithm (ACM) for complexes detection in PPI networks. ACM method contains of three stages. Firstly, we make use of PPI network topology, i.e., average degree, to present a new quantitative function and then present a hierarchical algorithm to identify protein complexes. Finally, post-processing is applied to the predicted results to ensure the accuracy and reliability. We experimentally evaluate the performance of ACM using three different yeast PPI networks. Our results show that ACM is effective and reliable in detecting protein complexes.
Keywords :
bioinformatics; data mining; pattern clustering; proteins; proteomics; ACM method; PPI network topology; average-degree based cluster mining algorithm; hierarchical algorithm; protein complexes identification; protein-protein interaction networks; Chromium; Clustering algorithms; Computer networks; Computer science; Cost function; Fungi; Network topology; Partitioning algorithms; Proteins; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on
Conference_Location :
Chengdu
ISSN :
2151-7614
Print_ISBN :
978-1-4244-4712-1
Electronic_ISBN :
2151-7614
Type :
conf
DOI :
10.1109/ICBBE.2010.5516601
Filename :
5516601
Link To Document :
بازگشت