High-accuracy splice site prediction based on sequence component and position features

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High-accuracy splice site prediction based on sequence component and position features.

Identification of splice sites plays a key role in the annotation of genes. Consequently, improvement of computational prediction of splice sites would be very useful. We examined the effect of the window size and the number and position of the consensus bases with a chi-square test, and then extracted the sequence multi-scale component features and the position and adjacent position relat...

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DNA Encoding for Splice Site Prediction in Large DNA Sequence

Splice site prediction in the pre-mRNA is a very important task for understanding gene structure and its function. To predict splice sites, SVM (support vector machine) based classification technique is frequently used because of its classification accuracy. High classification accuracy of SVM largely depends on DNA encoding method for feature extraction of DNA sequences. However, existing enco...

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A High Recall DNA Splice Site Prediction Based on Association Analysis

Genes in complex organisms such as primates and humans are composed of regions that code for protein creation, called exons, and non-coding regions, called introns. During the transcription from the DNA template for later translating into amino acid chain of protein structure, introns are to be removed and exons are then joined to form a continuous messenger-RNA strand. Splice sites are the jun...

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Evaluating the Accuracy of Splice Site Prediction based on Integrating Jensen-Shannon Divergence and a Polynomial Equation of Order 2

Advances in DNA sequencing technology have caused generation of the vast amount of new sequence data. It is essential to understand the functions, features, and structures of every newly sequenced data. Analyzing sequence data by different methods could provide important information about the sequence data. One of the essential tasks for genome annotation is gene prediction that can help to und...

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Feature subset selection for splice site prediction

MOTIVATION The large amount of available annotated Arabidopsis thaliana sequences allows the induction of splice site prediction models with supervised learning algorithms (see Haussler (1998) for a review and references). These algorithms need information sources or features from which the models can be computed. For splice site prediction, the features we consider in this study are the presen...

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ژورنال

عنوان ژورنال: Genetics and Molecular Research

سال: 2012

ISSN: 1676-5680

DOI: 10.4238/2012.september.25.12