Detection Using Principle Component Analysis And Case...
Splice site detection using principle component analysis and case based reasoning
with support vector machine
Srabanti Maji*1 and Haripada Bhunia2
1 Computer Science Department
Sri Guru Harkrishan College of Management and Technology, Raipur, Bahadurgarh;
Dist: Patiala,Punjab, India
2 Department of Chemical Engineering
Thapar University, Patiala 147004, India
*Address Correspondence to this author at
Dr. Srabanti Maji
Computer Science Department,
Sri Guru Harkrishan College of Management and Technology, Raipur, Bahadurgarh;
District: Patiala, Punjab, India
E mail address:
[email protected],
[email protected]
Tel: +91 9356006454
ABSTRACT
Identification of coding region from genomic DNA sequence is the foremost step ...
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feature selection; and the final stage, in which a support vector machine (SVM) with
Polynomial kernel is used for final classification. In comparison with other methods,
the proposed SpliceCombo model outperforms other prediction models as the
prediction accuracies are 97.25% sensitivity, 97.46% Specificity for donor splice site
and 96.51% Sensitivity, 94.48% Specificity for acceptor splice site prediction.
Keywords: Gene Identification, Splicing Site, Principal Component Analysis (PCA);
Cased Based Reasoning (CBR); Support Vector Machine(SVM)
*Correspondence to Srabanti Maji,
E mail address:
[email protected],
[email protected]
Tel: +91 9356006454
Splice site detection using principle component analysis and case based reasoning
with support vector machine
1.INTRODUCTION
Research in the genome sequencing technology have been creating an enormous
amount of genomic sequencing data as its main objective is gene identification. In
the eukaryotes, the prediction of a coding region depends upon the exon intron