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Updated: Feb 22, 2026

Enriching Subcellular Proteins in Leptospira Using a Triton X-114-Based Fractionation Approach
Published on: August 8, 2025
[Prediction of protein subcellular locations by ensemble of improved K-nearest neighbor]
Wei Xue1, Xiongfei Wang1, Nan Zhao1
1School of Information Science and Technology, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China.
Abstract:
Adaboost algorithm with improved K-nearest neighbor classifiers is proposed to predict protein subcellular locations. Improved K-nearest neighbor classifier uses three sequence feature vectors including amino acid composition, dipeptide and pseudo amino acid composition of protein sequence. K-nearest neighbor uses Blast in classification stage. The overall success rates by the jackknife test on two data sets of CH317 and Gram1253 are 92.4% and 93.1%. Adaboost algorithm with the novel K-nearest neighbor improved by Blast is an effective method for predicting subcellular locations of proteins.
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