Authors: Dolly Sharma; Sanguthevar Rajasekaran; Sudipta Pathak
Addresses: Amity University, Noida 201303, India ' Department of Computer Science and Engineering, University of Connecticut, Storrs 06269, CT, USA ' Department of Computer Science and Engineering, University of Connecticut, Storrs 06269, CT, USA
Abstract: A comparative study of the various motif search algorithms is very important for several reasons. For example, we could identify the strengths and weaknesses of each. As a result, we might be able to devise hybrids that will perform better than the individual components. In this paper, we (either directly or indirectly) compare the performance of PMSprune (an algorithm based on the (l, d)-motif model) and several other algorithms in terms of seven measures and using well-established benchmarks. We have employed several benchmark datasets including the one used by Tompa et al. It is observed that both PMSprune and DME (an algorithm based on position-specific score matrices), in general, perform better than the 13 algorithms reported in Tompa et al. Subsequently, we have compared PMSprune and DME on other benchmark datasets including ChIP-Chip, ChIP-Seq and ABS. Between PMSprune and DME, PMSprune performs better than DME on six measures. DME performs better than PMSprune on one measure (namely, specificity).
Keywords: statistical analysis; motif search algorithms; experimental comparison; bioinformatics.
International Journal of Bioinformatics Research and Applications, 2014 Vol.10 No.6, pp.559 - 573
Available online: 20 Oct 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article