Splice sites prediction of human genome using AdaBoost

Elham Pashaei; Mustafa Ozen; Nizamettin Aydin

doi:10.1109/BHI.2016.7455894

Splice sites prediction of human genome using AdaBoost

Elham Pashaei^*, Mustafa Ozen, Nizamettin Aydin

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Citations (Scopus)

Abstract

With the rapid growth of huge amounts of DNA sequence, gene prediction has become a challenging problem in bioinformatics. Splice sites prediction plays a key role in identification of genes. Hence, development of new methods to improve the accuracy of the splice sites prediction has great significance. This paper introduces a new method for splice sites prediction by combining AdaBoost classifier with a modified nucleotide encoding method, namely DM2. This method has been applied to the HS3D dataset with repeated 10-fold cross validation. Experimental results show that this method improves accuracy of the splice sites prediction and performs better than the MM1-SVM, Reduced MM1-SVM, SVM-B, LVMM2 and DM-SVM.

Original language	English
Title of host publication	3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	300-303
Number of pages	4
ISBN (Electronic)	9781509024551
DOIs	https://doi.org/10.1109/BHI.2016.7455894
Publication status	Published - 18 Apr 2016
Externally published	Yes
Event	3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016 - Las Vegas, United States Duration: 24 Feb 2016 → 27 Feb 2016

Publication series

Name	3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016

Conference

Conference	3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
Country/Territory	United States
City	Las Vegas
Period	24/02/16 → 27/02/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

AdaBoost classifier
Nucleotide encoding method
Splice site prediction

Access to Document

10.1109/BHI.2016.7455894

Cite this

Pashaei, E., Ozen, M., & Aydin, N. (2016). Splice sites prediction of human genome using AdaBoost. In 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016 (pp. 300-303). Article 7455894 (3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BHI.2016.7455894

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title = "Splice sites prediction of human genome using AdaBoost",

abstract = "With the rapid growth of huge amounts of DNA sequence, gene prediction has become a challenging problem in bioinformatics. Splice sites prediction plays a key role in identification of genes. Hence, development of new methods to improve the accuracy of the splice sites prediction has great significance. This paper introduces a new method for splice sites prediction by combining AdaBoost classifier with a modified nucleotide encoding method, namely DM2. This method has been applied to the HS3D dataset with repeated 10-fold cross validation. Experimental results show that this method improves accuracy of the splice sites prediction and performs better than the MM1-SVM, Reduced MM1-SVM, SVM-B, LVMM2 and DM-SVM.",

keywords = "AdaBoost classifier, Nucleotide encoding method, Splice site prediction",

author = "Elham Pashaei and Mustafa Ozen and Nizamettin Aydin",

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doi = "10.1109/BHI.2016.7455894",

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series = "3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016",

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Pashaei, E, Ozen, M & Aydin, N 2016, Splice sites prediction of human genome using AdaBoost. in 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016., 7455894, 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016, Institute of Electrical and Electronics Engineers Inc., pp. 300-303, 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016, Las Vegas, United States, 24/02/16. https://doi.org/10.1109/BHI.2016.7455894

Splice sites prediction of human genome using AdaBoost. / Pashaei, Elham; Ozen, Mustafa; Aydin, Nizamettin.
3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 300-303 7455894 (3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Splice sites prediction of human genome using AdaBoost

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AU - Ozen, Mustafa

AU - Aydin, Nizamettin

PY - 2016/4/18

Y1 - 2016/4/18

N2 - With the rapid growth of huge amounts of DNA sequence, gene prediction has become a challenging problem in bioinformatics. Splice sites prediction plays a key role in identification of genes. Hence, development of new methods to improve the accuracy of the splice sites prediction has great significance. This paper introduces a new method for splice sites prediction by combining AdaBoost classifier with a modified nucleotide encoding method, namely DM2. This method has been applied to the HS3D dataset with repeated 10-fold cross validation. Experimental results show that this method improves accuracy of the splice sites prediction and performs better than the MM1-SVM, Reduced MM1-SVM, SVM-B, LVMM2 and DM-SVM.

AB - With the rapid growth of huge amounts of DNA sequence, gene prediction has become a challenging problem in bioinformatics. Splice sites prediction plays a key role in identification of genes. Hence, development of new methods to improve the accuracy of the splice sites prediction has great significance. This paper introduces a new method for splice sites prediction by combining AdaBoost classifier with a modified nucleotide encoding method, namely DM2. This method has been applied to the HS3D dataset with repeated 10-fold cross validation. Experimental results show that this method improves accuracy of the splice sites prediction and performs better than the MM1-SVM, Reduced MM1-SVM, SVM-B, LVMM2 and DM-SVM.

KW - AdaBoost classifier

KW - Nucleotide encoding method

KW - Splice site prediction

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DO - 10.1109/BHI.2016.7455894

M3 - Conference contribution

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SP - 300

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BT - 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016

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ER -

Pashaei E, Ozen M, Aydin N. Splice sites prediction of human genome using AdaBoost. In 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 300-303. 7455894. (3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016). doi: 10.1109/BHI.2016.7455894

Splice sites prediction of human genome using AdaBoost

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Keywords

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