Splice sites prediction of Human genome using AdaBoost

Pashaei E., Ozen M., AYDIN N.

3rd IEEE EMBS International Conference on Biomedical and Health Informatics (IEEE BHI), Nevada, United States Of America, 24 - 27 February 2016, pp.300-303 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Nevada
  • Country: United States Of America
  • Page Numbers: pp.300-303
  • Keywords: Splice site prediction, AdaBoost classifier, Nucleotide encoding method, ALGORITHM
  • Kocaeli University Affiliated: No


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 (HSD)-D-3 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.