De novo Motif Prediction using the Fireworks Algorithm

Andrei Lihu and Ștefan Holban
Additional contact information
Andrei Lihu: Politehnica University of Timișoara, Timișoara, Romania
Ștefan Holban: Politehnica University of Timișoara, Timișoara, Romania

International Journal of Swarm Intelligence Research (IJSIR), 2015, vol. 6, issue 3, 24-40

Abstract: De novo motif discovery is essential in understanding the cis-regulatory processes that play a role in gene expression. Finding unknown patterns of unknown lengths in massive amounts of data has long been a major challenge in computational biology. Because algorithms for motif prediction have always suffered of low performance issues, there is a constant effort to find better techniques. Evolutionary methods, including swarm intelligence algorithms, have been applied with limited success for motif prediction. However, recently developed methods, such as the Fireworks Algorithm (FWA) which simulates the explosion process of fireworks, may show better prospects. This paper describes a motif finding algorithm based on FWA that maximizes the Kullback-Leibler divergence between candidate solutions and the background noise. Following the terminology of FWA's framework, the candidate motifs are fireworks that generate additional sparks (i.e. derived motifs) in their neighborhood. During the iterations, better sparks can replace the fireworks, as the Fireworks Motif Finder (FW-MF) assumes a one occurrence per sequence mode. The results obtained on a standard benchmark for promoter analysis show that our proof of concept is promising.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJSIR.2015070102 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jsir00:v:6:y:2015:i:3:p:24-40

Access Statistics for this article

International Journal of Swarm Intelligence Research (IJSIR) is currently edited by Yuhui Shi

More articles in International Journal of Swarm Intelligence Research (IJSIR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().