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Neural Computing and Applications
Published in: Neural Computing and Applications 7/2018

06-03-2018 | Original Article

A developed system based on nature-inspired algorithms for DNA motif finding process

Authors: Mai S. Mabrouk, Mohamed B. Abdelhalim, Ebtehal S. Elewa

Published in: Neural Computing and Applications | Issue 7/2018

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Abstract

In this paper, recent algorithms are suggested to repair the issue of motif finding. The proposed algorithms are cuckoo search, modified cuckoo search and finally a hybrid of gravitational search and particle swarm optimization algorithm. Motif finding is the technique of handling expressive motifs successfully in huge DNA sequences. DNA motif finding is important because it acts as a significant function in understanding the approach of gene regulation. Recent results of existing motifs finding programs display low accuracy and can not be used to find motifs in different types of datasets. Practical tests are implemented first on synthetic datasets and then on benchmark real datasets that are based on nature-inspired algorithms. The results revealed that the hybridization of gravitational search algorithm and particle swarm algorithms provides higher precision and recall values and provides average enhancement of F-score up to 0.24, compared to other existing algorithms and tools, and also that cuckoo search and modified cuckoo search have been able to successfully locate motifs in DNA sequences.
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Metadata
Title
A developed system based on nature-inspired algorithms for DNA motif finding process
Authors
Mai S. Mabrouk
Mohamed B. Abdelhalim
Ebtehal S. Elewa
Publication date
06-03-2018
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 7/2018
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3398-0

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