Frontiers of Information Technology & Electronic Engineering
>> 2015,
Volume 16,
Issue 4
doi:
10.1631/FITEE.1400282
Overlap maximum matching ratio (OMMR): a new measure to evaluate overlaps of essential modules
1. Department of Mathematics and Computer Science, Changsha University, Changsha 410003, China.2. School of Information Science and Engineering, Central South University, Changsha 410083, China
Available online: 2015-04-14
Next
Previous
Abstract
Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell’s mechanism. The development of the yeast two-hybrid, tandem affinity purification, and mass spectrometry high-throughput proteomic techniques supplies a large amount of protein-protein interaction data, which make it possible to predict overlapping complexes through computational methods. Research shows that overlapping complexes can contribute to identifying essential proteins, which are necessary for the organism to survive and reproduce, and for life’s activities. Scholars pay more attention to the evaluation of protein complexes. However, few of them focus on predicted overlaps. In this paper, an evaluation criterion called overlap maximum matching ratio (OMMR) is proposed to analyze the similarity between the identified overlaps and the benchmark overlap modules. Comparison of essential proteins and gene ontology (GO) analysis are also used to assess the quality of overlaps. We perform a comprehensive comparison of serveral overlapping complexes prediction approaches, using three yeast protein-protein interaction (PPI) networks. We focus on the analysis of overlaps identified by these algorithms. Experimental results indicate the important of overlaps and reveal the relationship between overlaps and identification of essential proteins.
京公网安备 11010502051620号
