title: Prediction of protein subcellular locations using Markov chain models.
abstract: A novel method was introduced to predict protein subcellular locations from sequences. Using sequence data, this method achieved a prediction accuracy higher than previous methods based on the amino acid composition. For three subcellular locations in a prokaryotic organism, the overall prediction accuracy reached 89.1%. For eukaryotic proteins, prediction accuracies of 73.0% and 78.7% were attained within four and three location categories, respectively. These results demonstrate the applicability of this relative simple method and possible improvement of prediction for the protein subcellular location.
authors.affiliation: National Laboratory of Biomacromolecules, Institute of Biophysics, Academia Sinica, Beijing, China. zxwang@sun5.ibp.ac.cn
authors.forename: Z
authors.initials: Z
authors.lastname: Yuan
mesh_terms: D008390:Markov Chains; D008954:Models, Biological; D011506:Proteins / Q000032:analysis*; D013347:Subcellular Fractions
chemical_list: D011506:Proteins