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Evaluation of the Occurrence Possibility of SNP in Brassica napus with Sliding Window Features by Using RBF Networks 被引量:2

Evaluation of the Occurrence Possibility of SNP in Brassica napus with Sliding Window Features by Using RBF Networks
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摘要 We extract some physical and chemical features re-lated to the occurrence of single nucleotide polymorphism (SNP) from three groups of sliding windows around SNP site,and then make the predictions about accuracy by using radial basis function (RBF) networks. The result of the forward sliding windows sug-gests that the accuracies and Matthews correlation coefficient (MCC values) ascend with the increasing of length of sliding windows. The accuracies range from 73.27 % to 80.69 %,and MCC values range from 0.465 to 0.614. The backward sliding windows and the sliding windows with fixed length three are de-signed to find the crucial sites related to SNP. The results imply that the occurrence possibility of SNP relies heavily on the above physical and chemical features of sites which are at a distance around 20 bases from the SNP site. Compared with the support vector machine (SVM),our RBF network approach has achieved more satisfactory results. We extract some physical and chemical features re-lated to the occurrence of single nucleotide polymorphism (SNP) from three groups of sliding windows around SNP site,and then make the predictions about accuracy by using radial basis function (RBF) networks. The result of the forward sliding windows sug-gests that the accuracies and Matthews correlation coefficient (MCC values) ascend with the increasing of length of sliding windows. The accuracies range from 73.27 % to 80.69 %,and MCC values range from 0.465 to 0.614. The backward sliding windows and the sliding windows with fixed length three are de-signed to find the crucial sites related to SNP. The results imply that the occurrence possibility of SNP relies heavily on the above physical and chemical features of sites which are at a distance around 20 bases from the SNP site. Compared with the support vector machine (SVM),our RBF network approach has achieved more satisfactory results.
出处 《Wuhan University Journal of Natural Sciences》 CAS 2011年第1期73-78,共6页 武汉大学学报(自然科学英文版)
基金 Supported by Discipline-Crossing Research Foundation of Huazhong Agricultural University(2008XKJC006) the Fundamental Research Funds for the Central Universities of China
关键词 single nucleotide polymorphism (SNP) radial basis function (RBF) network Brassica napus sliding windows single nucleotide polymorphism (SNP) radial basis function (RBF) network Brassica napus sliding windows
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