Title :
Detection of overlapping protein complexes using a protein ranking algorithm
Author_Institution :
Coll. of Inf. Technol., United Arab Emirates Univ., Al Ain, United Arab Emirates
Abstract :
The detection of protein complexes is evidently a cornerstone of understanding various biological processes and identifying key genes causing different diseases. Accordingly, many methods aiming at detecting protein complexes were developed. Recently, a novel method called ProRank was introduced. This method uses a ranking algorithm to detect protein complexes by ordering proteins based on their importance in the interaction network and by accounting for the evolutionary relationships among them. The experimental results showed that ProRank outperformed several well-known methods in terms of the number of detected complexes with high accuracy, precision and recall levels. In this paper, we overcome a drawback of the ProRank algorithm and further improve its performance by allowing detected protein complexes to overlap; a supposition that was not considered in the original version of the method.
Keywords :
biology computing; proteins; ProRank algorithm; biological process; disease; evolutionary relationships; interaction network; key gene identification; overlapping protein complex detection; protein ranking algorithm; Bioinformatics; Bridges; Educational institutions; Filtering; Google; Information technology; Proteins; PageRank algorithm; essential protein; overlapping protein complexes; protein-protein interaction;
Conference_Titel :
Innovations in Information Technology (IIT), 2013 9th International Conference on
Conference_Location :
Abu Dhabi
DOI :
10.1109/Innovations.2013.6544424