Network Motif Detection in PPI Networks and Effect of R Parameter on System Performance

Yilmaz Atay; Halife Kodaz

doi:10.18100/ijamec.05406

Research ArticlesverifiedPeer-ReviewedOpen Access

Pages: 78-82

Network Motif Detection in PPI Networks and Effect of R Parameter on System Performance

Yilmaz Atay •

Halife Kodaz

Publication DateAugust 28, 2016

Volume / IssueVol. 4, No. 3 (pp. 78-82)

DOI Identifier10.18100/ijamec.05406

subject

Abstract

Bioinformatics is an area on which lots of researches have been done and it is used widely in drug design, cancer treatment, disease detection, functional analysis, phylogenetic research and food and cell mutation changes. The field benefits from the partnership of disciplines like computer science, biology, genetics, mathematics and statistics. The incredible rise in areas of computer science such as artificial intelligence, graph theory, software and hardware technology and kind of has provided also a direct contribution to Bioinformatics. The subject of this study is to examine the FANMOD tool which discovers and analyses network motifs and to carry out performance analysis which is depending on the R (number of random networks) parameter. Four different protein-protein interaction ( PPI ) networks were used in the experiments. The R parameter used in the experiments were taken as 100, 1000, 10000 and 100000 and the obtained results are presented both graphically and quantitatively. Furthermore the average experiment time of each network and characteristic features of the obtained motifs are given at the end of the paper.

Keywords:BioinformaticsComplex networksFANMODGraph isomorphismNetwork motif detectionProtein-protein interaction networksSystem performance analysis

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Network Motif Detection in PPI Networks and Effect of R Parameter on System Performance

Abstract

References (13)

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