title: Prediction of N-terminal protein sorting signals.
abstract: Recently, neural networks have been applied to a widening range of problems in molecular biology. An area particularly suited to neural-network methods is the identification of protein sorting signals and the prediction of their cleavage sites, as these functional units are encoded by local, linear sequences of amino acids rather than global 3D structures.
authors.affiliation: Laboratorio de Bioqumica y Biologa Molecular, Facultad de Ciencias, Universidad de Málaga, Spain.
authors.forename: M G
authors.initials: MG
authors.lastname: Claros
authors.forename: S
authors.initials: S
authors.lastname: Brunak
authors.forename: G
authors.initials: G
authors.lastname: von Heijne
mesh_terms: D002736:Chloroplasts / Q000378:metabolism; D005544:Forecasting; D008928:Mitochondria / Q000378:metabolism; D008954:Models, Biological; D016571:Neural Networks, Computer; D010446:Peptide Fragments / Q000737:chemistry / Q000378:metabolism; D021382:Protein Sorting Signals; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*
chemical_list: D010446:Peptide Fragments; D021382:Protein Sorting Signals; D011506:Proteins