Refractory effects of chaotic neurodynamics for finding motifs from DNA sequences

Takafumi Matsuura, Tohru Ikeguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

To discover a common and conserved pattern, or motif, from DNA sequences is an important step to analyze DNA sequences because the patterns are acknowledged to reflect biological important information. However, it is difficult to discover unknown motifs from DNA sequences because of its huge number of combination. We have already proposed a new effective method to extract the motifs using a chaotic search, which combines a heuristic algorithm and a chaotic dynamics. To realize the chaotic search, we used a chaotic neural network. The chaotic search exhibits higher performance than conventional methods. Although we have indicated that the refractory effects realized by the chaotic neural network have an essential role, we did not clarify why the refractory effects are important to search optimal solutions. In this paper, we further investigate this issue and reveal the validity of the refractory effects of the chaotic dynamics using surrogate refractory effects. As a result, we discovered that it is important for searching optimal solutions to increase strength of the refractory effects after a firing of neurons.

Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning, IDEAL 2006 - 7th International Conference, Proceedings
PublisherSpringer Verlag
Pages1103-1110
Number of pages8
ISBN (Print)3540454853, 9783540454854
Publication statusPublished - 1 Jan 2006
Event7th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2006 - Burgos, Spain
Duration: 20 Sep 200623 Sep 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4224 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2006
CountrySpain
CityBurgos
Period20/09/0623/09/06

    Fingerprint

Cite this

Matsuura, T., & Ikeguchi, T. (2006). Refractory effects of chaotic neurodynamics for finding motifs from DNA sequences. In Intelligent Data Engineering and Automated Learning, IDEAL 2006 - 7th International Conference, Proceedings (pp. 1103-1110). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4224 LNCS). Springer Verlag.