title: Prediction of subcellular locations of proteins: where to proceed?
abstract: Since the proposal of the signal hypothesis on protein subcellular sorting, a number of computational analyses have been performed in this field. A typical example is the development of prediction algorithms for the subcellular localization sites of input protein sequences. In this review, we mainly focus on the biological grounds of the prediction methods rather than the algorithmic issues because we believe the former will be more fruitful for future development. Recent advances on the study of protein sorting signals will hopefully be incorporated into future prediction methods. Unfortunately, many of the state-of-the-art methods are published without sufficient objective tests. In fact, a simple test employed in this article shows that the performance of specifically developed predictors is not significantly better than that of a homology search. We suspect that this is a general problem associated with the interpretation of genome sequences, which have evolved through gene duplication and speciation.
authors.affiliation: Computational Biology Research Center, AIST, Tokyo, Japan.
authors.forename: Kenichiro
authors.initials: K
authors.lastname: Imai
authors.forename: Kenta
authors.initials: K
authors.lastname: Nakai
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D021382:Protein Sorting Signals; D011506:Proteins / Q000378:metabolism*; D040901:Proteomics
chemical_list: D021382:Protein Sorting Signals; D011506:Proteins