Strategies for Network Motifs Discovery

• Type: Article in International Conference Proceedings Book
• Date: 2009

Authors

Ribeiro, P (Author) Other; Silva, F (Author) FCUP; Kaiser, M (Author) Other

Conference proceedings International

Title: e-Science 2009 - 5th IEEE International Conference on e-Science

Pages: 80-87

Fifth International Conference on e-Science, e-Science 2009, 9-11 December 2009, Oxford, UK

Oxford, UK, 9-11 December 2009

Indexing

ISI Web of Knowledge

Scopus - 55 Citations

Other information

Authenticus ID: P-007-SR3

DOI: 10.1109/e-Science.2009.20

Abstract (EN): Complex networks from domains like Biology or Sociology are present in many e-Science data sets. Dealing with networks can often form a workflow bottleneck as several related algorithms are computationally hard. One example is detecting characteristic patterns or "network motifs" - a problem involving subgraph mining and graph isomorphism. This paper provides a review and runtime comparison of current motif detection algorithms in the field. We present the strategies and the corresponding algorithms in pseudo-code yielding a framework for comparison. We categorize the algorithms outlining the main differences and advantages of each strategy. We finally implement all strategies in a common platform to allow a fair and objective efficiency comparison using a set of benchmark networks.We hope to inform the choice of strategy and critically discuss future improvements in motif detection. © 2009 IEEE.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8