A novel method for splice sites prediction using sequence component and hidden Markov model

Elham Pashaei; Alper Yilmaz; Mustafa Ozen; Nizamettin Aydin

doi:10.1109/EMBC.2016.7591379

A novel method for splice sites prediction using sequence component and hidden Markov model

Elham Pashaei
, Alper Yilmaz
, Mustafa Ozen
, Nizamettin Aydin

Yildiz Technical University
Biruni Universitesi

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

10 Atıf (Scopus)

Özet

With increasing growth of DNA sequence data, it has become an urgent demand to develop new methods to accurately predict the genes. The performance of gene detection methods mainly depend on the efficiency of splice site prediction methods. In this paper, a novel method for detecting splice sites is proposed by using a new effective DNA encoding method and AdaBoost.M1 classifier. Our proposed DNA encoding method is based on multi-scale component (MSC) and first order Markov model (MM1). It has been applied to the HS3D dataset with repeated 10 fold cross validation. The experimental results indicate that the new method has increased the classification accuracy and outperformed some current methods such as MM1-SVM, Reduced MM1-SVM, SVM-B, LVMM, DM-SVM, DM2-AdaBoost and MS C+Pos(+APR)-SVM.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	3076-3079
Sayfa sayısı	4
ISBN (Elektronik)	9781457702204
DOI'lar	https://doi.org/10.1109/EMBC.2016.7591379
Yayın durumu	Yayınlandı - 13 Eki 2016
Harici olarak yayınlandı	Evet
Etkinlik	38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States Süre: 16 Ağu 2016 → 20 Ağu 2016

Yayın serisi

Adı	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Hacim	2016-October
ISSN (Basılı)	1557-170X

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Ülke/Bölge	United States
Şehir	Orlando
Periyot	16/08/16 → 20/08/16

Bibliyografik not

Publisher Copyright:
© 2016 IEEE.

Belgeye Erişim

10.1109/EMBC.2016.7591379

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Pashaei, E., Yilmaz, A., Ozen, M., & Aydin, N. (2016). A novel method for splice sites prediction using sequence component and hidden Markov model. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 (pp. 3076-3079). Makale 7591379 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Hac. 2016-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2016.7591379

Pashaei, Elham ; Yilmaz, Alper ; Ozen, Mustafa et al. / A novel method for splice sites prediction using sequence component and hidden Markov model. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 3076-3079 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

@inproceedings{a7653683e5d04edaabf0af62ff1469c5,

title = "A novel method for splice sites prediction using sequence component and hidden Markov model",

abstract = "With increasing growth of DNA sequence data, it has become an urgent demand to develop new methods to accurately predict the genes. The performance of gene detection methods mainly depend on the efficiency of splice site prediction methods. In this paper, a novel method for detecting splice sites is proposed by using a new effective DNA encoding method and AdaBoost.M1 classifier. Our proposed DNA encoding method is based on multi-scale component (MSC) and first order Markov model (MM1). It has been applied to the HS3D dataset with repeated 10 fold cross validation. The experimental results indicate that the new method has increased the classification accuracy and outperformed some current methods such as MM1-SVM, Reduced MM1-SVM, SVM-B, LVMM, DM-SVM, DM2-AdaBoost and MS C+Pos(+APR)-SVM.",

keywords = "AdaBoost.M1 classifier, DNA encoding method, Splice site prediction",

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

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 ; Conference date: 16-08-2016 Through 20-08-2016",

year = "2016",

month = oct,

day = "13",

doi = "10.1109/EMBC.2016.7591379",

language = "English",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

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

pages = "3076--3079",

booktitle = "2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016",

address = "United States",

}

Pashaei, E, Yilmaz, A, Ozen, M & Aydin, N 2016, A novel method for splice sites prediction using sequence component and hidden Markov model. in 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016., 7591379, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, hac. 2016-October, Institute of Electrical and Electronics Engineers Inc., pp. 3076-3079, 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016, Orlando, United States, 16/08/16. https://doi.org/10.1109/EMBC.2016.7591379

A novel method for splice sites prediction using sequence component and hidden Markov model. / Pashaei, Elham; Yilmaz, Alper; Ozen, Mustafa et al.
2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 3076-3079 7591379 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Hac. 2016-October).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - A novel method for splice sites prediction using sequence component and hidden Markov model

AU - Pashaei, Elham

AU - Yilmaz, Alper

AU - Ozen, Mustafa

AU - Aydin, Nizamettin

PY - 2016/10/13

Y1 - 2016/10/13

N2 - With increasing growth of DNA sequence data, it has become an urgent demand to develop new methods to accurately predict the genes. The performance of gene detection methods mainly depend on the efficiency of splice site prediction methods. In this paper, a novel method for detecting splice sites is proposed by using a new effective DNA encoding method and AdaBoost.M1 classifier. Our proposed DNA encoding method is based on multi-scale component (MSC) and first order Markov model (MM1). It has been applied to the HS3D dataset with repeated 10 fold cross validation. The experimental results indicate that the new method has increased the classification accuracy and outperformed some current methods such as MM1-SVM, Reduced MM1-SVM, SVM-B, LVMM, DM-SVM, DM2-AdaBoost and MS C+Pos(+APR)-SVM.

AB - With increasing growth of DNA sequence data, it has become an urgent demand to develop new methods to accurately predict the genes. The performance of gene detection methods mainly depend on the efficiency of splice site prediction methods. In this paper, a novel method for detecting splice sites is proposed by using a new effective DNA encoding method and AdaBoost.M1 classifier. Our proposed DNA encoding method is based on multi-scale component (MSC) and first order Markov model (MM1). It has been applied to the HS3D dataset with repeated 10 fold cross validation. The experimental results indicate that the new method has increased the classification accuracy and outperformed some current methods such as MM1-SVM, Reduced MM1-SVM, SVM-B, LVMM, DM-SVM, DM2-AdaBoost and MS C+Pos(+APR)-SVM.

KW - AdaBoost.M1 classifier

KW - DNA encoding method

KW - Splice site prediction

UR - https://www.scopus.com/pages/publications/85009080869

U2 - 10.1109/EMBC.2016.7591379

DO - 10.1109/EMBC.2016.7591379

M3 - Conference contribution

C2 - 28268961

AN - SCOPUS:85009080869

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 3076

EP - 3079

BT - 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016

Y2 - 16 August 2016 through 20 August 2016

ER -

Pashaei E, Yilmaz A, Ozen M, Aydin N. A novel method for splice sites prediction using sequence component and hidden Markov model. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 3076-3079. 7591379. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2016.7591379

A novel method for splice sites prediction using sequence component and hidden Markov model

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Bibliyografik not

Belgeye Erişim

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