Article
Partition dataset according to amino acid type improves the prediction of deleterious non-synonymous SNPs.
Biochemical and biophysical research communications - 2 Mar 2012
Yang Jing, Li Yuan-Yuan, Li Yi-Xue, Ye Zhi-Qiang
Abstract excerpt
Many non-synonymous SNPs (nsSNPs) are associated with diseases, and numerous machine learning methods have been applied to train classifiers for sorting disease-associated nsSNPs from neutral ones. The continuously accumulated nsSNP data allows us to further explore better prediction approaches. In this work, we partitioned the training data into 20 subsets according to either original or substituted amino acid...
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