Please use this identifier to cite or link to this item: https://doi.org/10.1504/IJVD.2005.007220
Title: Feature selection for the prediction of translation initiation sites
Authors: Li, G.-L. 
Leong, T.-Y. 
Keywords: Classification
Feature selection
Translation initiation site prediction
Issue Date: 2005
Source: Li, G.-L., Leong, T.-Y. (2005). Feature selection for the prediction of translation initiation sites. Genomics, Proteomics and Bioinformatics 3 (2) : 73-83. ScholarBank@NUS Repository. https://doi.org/10.1504/IJVD.2005.007220
Abstract: Translation initiation sites (TISs) are important signals in cDNA sequences. In many previous attempts to predict TISs in cDNA sequences, three major factors affect the prediction performance: the nature of the cDNA sequence sets, the relevant features selected, and the classification methods used. In this paper, we examine different approaches to select and integrate relevant features for TIS prediction. The top selected significant features include the features from the position weight matrix and the propensity matrix, the number of nucleotide C in the sequence downstream ATG, the number of downstream stop codons, the number of upstream ATGs, and the number of some amino acids, such as amino acids A and D. With the numerical data generated from these features, different classification methods, including decision tree, naïve Bayes, and support vector machine, were applied to three independent sequence sets. The identified significant features were found to be biologically meaningful, while the experiments showed promising results.
Source Title: Genomics, Proteomics and Bioinformatics
URI: http://scholarbank.nus.edu.sg/handle/10635/39235
ISSN: 16720229
DOI: 10.1504/IJVD.2005.007220
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