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Due to an exponential increase in biological sequence data, gene detection has become one of the challenging tasks in computational biology. Splice site prediction is an essential part of the gene detection. Thus, it has great significance to develop efficient methods for accurately identifying splice sites. This paper introduces a novel algorithm to predict the splice sites based on support vector...
The Biological sequence data are increasing rapidly, so there is a vital need of effective method for gene detection. Predicting of splice site is an important part of gene finding. Therefore, attempts to improve the prediction accuracy of the computational methods for splice sites detection continue. In this paper we propose a hybrid algorithm for splice sites prediction by combining AdaBoost classifier...
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...
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