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Support vector machine approach for protein subcellular localization prediction
2001
Bioinformatics
Motivation: Subcellular localization is a key functional characteristic of proteins. A fully automatic and reliable prediction system for protein subcellular localization is needed, especially for the analysis of large-scale genome sequences. Results: In this paper, Support Vector Machine has been introduced to predict the subcellular localization of proteins from their amino acid compositions. The total prediction accuracies reach 91.4% for three subcellular locations in prokaryotic organisms
doi:10.1093/bioinformatics/17.8.721
pmid:11524373
fatcat:bnvkqa7sdzf3hgz47lqi3yeb5u