Cover Image

Modelling complex features from histone modification signatures using genetic algorithm for the prediction of enhancer region

Using Genetic Algorithm, this paper presents a modelling method to generate novel logical-based features from DNA sequences enriched with H3K4mel histone signatures. Current histone signature is mostly represented using k-mers content features incapable of representing all the possible complex inte...

Full description

Saved in:
Bibliographic Details
Main Authors: Lee, Nung Kion, Fong, Pui Kwan, Mohd Tajuddin, Abdullah
Format: Article
Language:English
Published: IOS Press 2014
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://ir.unimas.my/id/eprint/31049/1/Lee%20Nung%20Kion.pdf
http://ir.unimas.my/id/eprint/31049/
https://content.iospress.com/articles/bio-medical-materials-and-engineering/bme1210
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimas.ir.31049
record_format eprints
spelling my.unimas.ir.310492022-01-26T01:53:37Z http://ir.unimas.my/id/eprint/31049/ Modelling complex features from histone modification signatures using genetic algorithm for the prediction of enhancer region Lee, Nung Kion Fong, Pui Kwan Mohd Tajuddin, Abdullah QA75 Electronic computers. Computer science Using Genetic Algorithm, this paper presents a modelling method to generate novel logical-based features from DNA sequences enriched with H3K4mel histone signatures. Current histone signature is mostly represented using k-mers content features incapable of representing all the possible complex interactions of various DNA segments. The main contributions are, among others: (a) demonstrating that there are complex interactions among sequence segments in the histone regions; (b) developing a parse tree representation of the logical complex features. The proposed novel feature is compared to the k-mers content features using datasets from the mouse (mm9) genome. Evaluation results show that the new feature improves the prediction performance as shown by f-measure for all datasets tested. Also, it is discovered that treebased features generated from a single chromosome can be generalized to predict histone marks in other chromosomes not used in the training. These findings have a great impact on feature design considerations for histone signatures as well as other classifier design features. IOS Press 2014 Article PeerReviewed text en http://ir.unimas.my/id/eprint/31049/1/Lee%20Nung%20Kion.pdf Lee, Nung Kion and Fong, Pui Kwan and Mohd Tajuddin, Abdullah (2014) Modelling complex features from histone modification signatures using genetic algorithm for the prediction of enhancer region. Bio-Medical Materials and Engineering, 24 (6). pp. 3807-3814. ISSN 0959-2989 https://content.iospress.com/articles/bio-medical-materials-and-engineering/bme1210 DOI 10.3233/BME-141210
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Lee, Nung Kion
Fong, Pui Kwan
Mohd Tajuddin, Abdullah
Modelling complex features from histone modification signatures using genetic algorithm for the prediction of enhancer region
description Using Genetic Algorithm, this paper presents a modelling method to generate novel logical-based features from DNA sequences enriched with H3K4mel histone signatures. Current histone signature is mostly represented using k-mers content features incapable of representing all the possible complex interactions of various DNA segments. The main contributions are, among others: (a) demonstrating that there are complex interactions among sequence segments in the histone regions; (b) developing a parse tree representation of the logical complex features. The proposed novel feature is compared to the k-mers content features using datasets from the mouse (mm9) genome. Evaluation results show that the new feature improves the prediction performance as shown by f-measure for all datasets tested. Also, it is discovered that treebased features generated from a single chromosome can be generalized to predict histone marks in other chromosomes not used in the training. These findings have a great impact on feature design considerations for histone signatures as well as other classifier design features.
format Article
author Lee, Nung Kion
Fong, Pui Kwan
Mohd Tajuddin, Abdullah
author_facet Lee, Nung Kion
Fong, Pui Kwan
Mohd Tajuddin, Abdullah
author_sort Lee, Nung Kion
title Modelling complex features from histone modification signatures using genetic algorithm for the prediction of enhancer region
title_short Modelling complex features from histone modification signatures using genetic algorithm for the prediction of enhancer region
title_full Modelling complex features from histone modification signatures using genetic algorithm for the prediction of enhancer region
title_fullStr Modelling complex features from histone modification signatures using genetic algorithm for the prediction of enhancer region
title_full_unstemmed Modelling complex features from histone modification signatures using genetic algorithm for the prediction of enhancer region
title_sort modelling complex features from histone modification signatures using genetic algorithm for the prediction of enhancer region
publisher IOS Press
publishDate 2014
url http://ir.unimas.my/id/eprint/31049/1/Lee%20Nung%20Kion.pdf
http://ir.unimas.my/id/eprint/31049/
https://content.iospress.com/articles/bio-medical-materials-and-engineering/bme1210
_version_ 1724078524303671296
score 13.211869

Similar Items