loading
Documents

Research.Publish.Connect.

Paper

Classification of Helitron’s Types in the C.elegans Genome based on Features Extracted from Wavelet Transform and SVM Methods

Topics: Computational Intelligence; Computational Molecular Systems; Image Analysis; Pattern Recognition, Clustering and Classification; Sequence Analysis; Structural Bioinformatics; Structure Prediction; Visualization

Authors: Rabeb Touati ; Imen Messaoudi ; Afef ElloumiOueslati and Zied Lachiri

Affiliation: University of Tunis el Manar and National Engineering School, Tunisia

ISBN: 978-989-758-280-6

ISSN: 2184-4305

Keyword(s): Transposable Elements (TES), Helitrons, C.elegans, SVM, Kernel-tricks, FCGS, CWT, Energy-wavelet.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Bioinformatics ; Biomedical Engineering ; Computational Intelligence ; Computational Molecular Systems ; Image Analysis ; Pattern Recognition, Clustering and Classification ; Sequence Analysis ; Soft Computing ; Structural Bioinformatics ; Structure Prediction ; Visualization

Abstract: Helitrons, a sub-class of the Transposable elements class 2, are considered as an important DNA type. In fact, they contribute in mechanism’s evolution. Till now, these elements are not well studied using the automatic tools. In fact, the researches done in helitron's recognition are based only on biological experiments. In this paper, we propose an automatic method for characterizing helitrons by global signature and classifying the helitron’s types in C.elegans genome. For this goal, we used the Complex Morlet Wavelet Transform to generate helitron’s signatures (helitron’s scalograms presentation) and to extract the features of each category. Then, we used the SVM-classifier to classify these 10 helitron’s families. After testing different kernels and using the cross validation function, we present the best classification results given by the RBF-kernel with c=60, σ=0. 0000000015625 and OAO approach.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.168.112.145

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Touati, R.; Messaoudi, I.; ElloumiOueslati, A. and Lachiri, Z. (2018). Classification of Helitron’s Types in the C.elegans Genome based on Features Extracted from Wavelet Transform and SVM Methods.In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3 BIOINFORMATICS: BIOINFORMATICS, ISBN 978-989-758-280-6, ISSN 2184-4305, pages 127-134. DOI: 10.5220/0006631001270134

@conference{bioinformatics18,
author={Rabeb Touati. and Imen Messaoudi. and Afef ElloumiOueslati. and Zied Lachiri.},
title={Classification of Helitron’s Types in the C.elegans Genome based on Features Extracted from Wavelet Transform and SVM Methods},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3 BIOINFORMATICS: BIOINFORMATICS,},
year={2018},
pages={127-134},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006631001270134},
isbn={978-989-758-280-6},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3 BIOINFORMATICS: BIOINFORMATICS,
TI - Classification of Helitron’s Types in the C.elegans Genome based on Features Extracted from Wavelet Transform and SVM Methods
SN - 978-989-758-280-6
AU - Touati, R.
AU - Messaoudi, I.
AU - ElloumiOueslati, A.
AU - Lachiri, Z.
PY - 2018
SP - 127
EP - 134
DO - 10.5220/0006631001270134

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.