Prediction of protein subcellular locations by similarity comparison

Abstract:

[Objective] A new subcellular location prediction algorithm is proposed that provides basis for further experimental study of protein biological function. [Methods] Nearest neighbor classification algorithm improved by Blast comparison is used to predict the protein subcellular locations by three sequence features including amino acid composition, two peptides and pseudo amino acid composition of protein sequence. [Results] Through Jackknife test, on data set CH317 the success rates of 3 characteristics were 91.5%, 91.5% and 89.3%, on data set ZD98 success rates were 93.9%, 92.9% and 89.8%. [Conclusion] K-Nearest Neighbor algorithm improved by Blast comparison is an effective method for predicting subcellular locations of proteins.