title: Predicting multisite protein subcellular locations: progress and challenges.
abstract: In the last two decades, predicting protein subcellular locations has become a hot topic in bioinformatics. A number of algorithms and online services have been developed to computationally assign a subcellular location to a given protein sequence. With the progress of many proteome projects, more and more proteins are annotated with more than one subcellular location. However, multisite prediction has only been considered in a handful of recent studies, in which there are several common challenges. In this special report, the authors discuss what these challenges are, why these challenges are important and how the existing studies gave their solutions. Finally, a vision of the future of predicting multisite protein subcellular locations is given.
authors.affiliation: School of Computer Science and Technology, Tianjin University, Tianjin 300072, China.
authors.forename: Pufeng
authors.initials: P
authors.lastname: Du
authors.forename: Chao
authors.initials: C
authors.lastname: Xu
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D021381:Protein Transport; D011506:Proteins / Q000378:metabolism*; D013347:Subcellular Fractions / Q000378:metabolism
chemical_list: D011506:Proteins