title: SubChlo: predicting protein subchloroplast locations with pseudo-amino acid composition and the evidence-theoretic K-nearest neighbor (ET-KNN) algorithm.
abstract: The chloroplast is a type of plant specific subcellular organelle. It is of central importance in several biological processes like photosynthesis and amino acid biosynthesis. Thus, understanding the function of chloroplast proteins is of significant value. Since the function of chloroplast proteins correlates with their subchloroplast locations, the knowledge of their subchloroplast locations can be very helpful in understanding their role in the biological processes. In the current paper, by introducing the evidence-theoretic K-nearest neighbor (ET-KNN) algorithm, we developed a method for predicting the protein subchloroplast locations. This is the first algorithm for predicting the protein subchloroplast locations. We have implemented our algorithm as an online service, SubChlo (http://bioinfo.au.tsinghua.edu.cn/subchlo). This service may be useful to the chloroplast proteome research.
authors.affiliation: MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China. dpf05@mails.tsinghua.edu.cn
authors.forename: Pufeng
authors.initials: P
authors.lastname: Du
authors.forename: Shengjiao
authors.initials: S
authors.lastname: Cao
authors.forename: Yanda
authors.initials: Y
authors.lastname: Li
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000032:analysis; D002736:Chloroplasts / Q000737:chemistry*; D009862:Online Systems; D010940:Plant Proteins / Q000032:analysis*; D020543:Proteome
chemical_list: D000596:Amino Acids; D010940:Plant Proteins; D020543:Proteome