title: Prediction of protein subcellular locations by support vector machines using compositions of amino acids and amino acid pairs.
abstract: BACKGROUND
  The subcellular location of a protein is closely correlated to its function. Thus, computational prediction of subcellular locations from the amino acid sequence information would help annotation and functional prediction of protein coding genes in complete genomes. We have developed a method based on support vector machines (SVMs).
  
  
  RESULTS
  We considered 12 subcellular locations in eukaryotic cells: chloroplast, cytoplasm, cytoskeleton, endoplasmic reticulum, extracellular medium, Golgi apparatus, lysosome, mitochondrion, nucleus, peroxisome, plasma membrane, and vacuole. We constructed a data set of proteins with known locations from the SWISS-PROT database. A set of SVMs was trained to predict the subcellular location of a given protein based on its amino acid, amino acid pair, and gapped amino acid pair compositions. The predictors based on these different compositions were then combined using a voting scheme. Results obtained through 5-fold cross-validation tests showed an improvement in prediction accuracy over the algorithm based on the amino acid composition only. This prediction method is available via the Internet.
authors.affiliation: Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.
authors.forename: Keun-Joon
authors.initials: KJ
authors.lastname: Park
authors.forename: Minoru
authors.initials: M
authors.lastname: Kanehisa
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry / Q000378:metabolism; D001185:Artificial Intelligence; D022082:Cellular Structures / Q000737:chemistry / Q000378:metabolism; D003205:Computing Methodologies; D030562:Databases, Protein; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D013347:Subcellular Fractions / Q000737:chemistry* / Q000378:metabolism*; D014018:Tissue Distribution
chemical_list: D000596:Amino Acids; D011506:Proteins