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

11 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

@inproceedings{f1af36e0802948839538915002870a08,

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",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016 ; Conference date: 24-02-2016 Through 27-02-2016",

year = "2016",

month = apr,

day = "18",

doi = "10.1109/BHI.2016.7455894",

language = "English",

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

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "300--303",

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

address = "United States",

}

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

AU - Pashaei, Elham

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

UR - http://www.scopus.com/inward/record.url?scp=84968537991&partnerID=8YFLogxK

U2 - 10.1109/BHI.2016.7455894

DO - 10.1109/BHI.2016.7455894

M3 - Conference contribution

AN - SCOPUS:84968537991

T3 - 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016

SP - 300

EP - 303

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

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016

Y2 - 24 February 2016 through 27 February 2016

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this