Prediction of subcellular locations of proteins: Where to proceed?
Identifieur interne : 002691 ( Main/Exploration ); précédent : 002690; suivant : 002692Prediction of subcellular locations of proteins: Where to proceed?
Auteurs : Kenichiro Imai [Japon] ; Kenta Nakai [Japon]Source :
- PROTEOMICS [ 1615-9853 ] ; 2010-11.
English descriptors
- Teeft :
- Algorithm, Amino, Amino acid composition, Amino acid residues, Amino acid sequence, Amino acid sequences, Amino acids, Annotation, Annotation information, Answer sets, Arabidopsis leaf peroxisomes, Bacterial protein subcellular localization, Bacterial protein transport, Bacterial proteins, Biochem, Bioinformatics, Biol, Biological grounds, Bipartite, Blast wolfpsort multiloc2, Cell biol, Chloroplast, Chloroplast transit peptides, Classical nlss, Cleavage, Cleavage site, Cleavage site motif, Cleavage sites, Consensus patterns, Consensus sequence, Consensus sequences, Correlated characteristics, Cytoplasmic membrane, Data sets, Database, Database issue, Different sites, Endoplasmic reticulum, Eukaryotic, Eukaryotic cells, Exit signal, Extracellular, Extracellular proteins, Extracellular space, Functional motifs, Gene ontology, Gene ontology terms, Genome, Global analysis, Gmbh, Heijne, Homology, Homology method, Homology search, Hybrid method, Identity components, Imai, Importin, Inherent problem, Input features, Input information, Intermembrane space, Intracellular loop, Kgaa, Large number, Linker length, Localization, Localization site, Localization sites, Long signal peptides, Lysosomal proteins, Many proteins, Matrix proteins, Matthews correlation, Mbomps, Medical science, Membrane, Membrane protein, Membrane protein topology, Membrane proteins, Membrane topology, Mitochondrial, Mitochondrial betabarrel proteins, Mitochondrial precursor proteins, Mitochondrial presequences, Mitochondrial processing peptidase, Mitochondrial proteins, Mitochondrion, More attention, Motif, Multiloc2, Nakai, Nlss, Novel proteins, Nuclear export signal, Nuclear export signals, Nuclear localization, Nuclear localization signals, Nuclear proteins, Nucleic, Nucleic acids, Objective test, Other hand, Other sources, Outer membrane, Outer membrane proteins, Pathway, Pattern recognition algorithms, Peptidase, Peptide, Peroxisomal, Peroxisomal membrane proteins, Plant cell, Plos pathog, Prediction, Prediction accuracy, Prediction algorithms, Prediction methods, Prediction performance, Predictor, Presequences, Processing peptidase, Proline, Protein, Protein localization, Protein localization sites, Protein subcellular localization, Protein subcellular localization prediction, Proteome, Proteome analysis, Proteomics, Psort, Public databases, Recent advances, Receptor, Secretion system, Secretory pathway, Sequence homology, Sequence motifs, Sequence patterns, Sequence similarity, Serine, Signal peptide, Signal peptide cleavage site, Signal peptides, Signal region, Signal sequences, Simple method, Simple test, Single residue, Special interest, Subcellular, Subcellular localization, Subcellular localization site, Subcellular localization sites, Subcellular locations, Support vector machines, Target database, Test sets, Topology, Training data, Transit peptides, Transmembrane domains, Trends cell biol, Typical example, Verlag, Verlag gmbh, Weinheim, Weinheim proteomics, Wolf psort, Yeast, Yeast chromosome.
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.
Url:
DOI: 10.1002/pmic.201000274
Affiliations:
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Le document en format XML
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<profileDesc><textClass><keywords scheme="Teeft" xml:lang="en"><term>Algorithm</term>
<term>Amino</term>
<term>Amino acid composition</term>
<term>Amino acid residues</term>
<term>Amino acid sequence</term>
<term>Amino acid sequences</term>
<term>Amino acids</term>
<term>Annotation</term>
<term>Annotation information</term>
<term>Answer sets</term>
<term>Arabidopsis leaf peroxisomes</term>
<term>Bacterial protein subcellular localization</term>
<term>Bacterial protein transport</term>
<term>Bacterial proteins</term>
<term>Biochem</term>
<term>Bioinformatics</term>
<term>Biol</term>
<term>Biological grounds</term>
<term>Bipartite</term>
<term>Blast wolfpsort multiloc2</term>
<term>Cell biol</term>
<term>Chloroplast</term>
<term>Chloroplast transit peptides</term>
<term>Classical nlss</term>
<term>Cleavage</term>
<term>Cleavage site</term>
<term>Cleavage site motif</term>
<term>Cleavage sites</term>
<term>Consensus patterns</term>
<term>Consensus sequence</term>
<term>Consensus sequences</term>
<term>Correlated characteristics</term>
<term>Cytoplasmic membrane</term>
<term>Data sets</term>
<term>Database</term>
<term>Database issue</term>
<term>Different sites</term>
<term>Endoplasmic reticulum</term>
<term>Eukaryotic</term>
<term>Eukaryotic cells</term>
<term>Exit signal</term>
<term>Extracellular</term>
<term>Extracellular proteins</term>
<term>Extracellular space</term>
<term>Functional motifs</term>
<term>Gene ontology</term>
<term>Gene ontology terms</term>
<term>Genome</term>
<term>Global analysis</term>
<term>Gmbh</term>
<term>Heijne</term>
<term>Homology</term>
<term>Homology method</term>
<term>Homology search</term>
<term>Hybrid method</term>
<term>Identity components</term>
<term>Imai</term>
<term>Importin</term>
<term>Inherent problem</term>
<term>Input features</term>
<term>Input information</term>
<term>Intermembrane space</term>
<term>Intracellular loop</term>
<term>Kgaa</term>
<term>Large number</term>
<term>Linker length</term>
<term>Localization</term>
<term>Localization site</term>
<term>Localization sites</term>
<term>Long signal peptides</term>
<term>Lysosomal proteins</term>
<term>Many proteins</term>
<term>Matrix proteins</term>
<term>Matthews correlation</term>
<term>Mbomps</term>
<term>Medical science</term>
<term>Membrane</term>
<term>Membrane protein</term>
<term>Membrane protein topology</term>
<term>Membrane proteins</term>
<term>Membrane topology</term>
<term>Mitochondrial</term>
<term>Mitochondrial betabarrel proteins</term>
<term>Mitochondrial precursor proteins</term>
<term>Mitochondrial presequences</term>
<term>Mitochondrial processing peptidase</term>
<term>Mitochondrial proteins</term>
<term>Mitochondrion</term>
<term>More attention</term>
<term>Motif</term>
<term>Multiloc2</term>
<term>Nakai</term>
<term>Nlss</term>
<term>Novel proteins</term>
<term>Nuclear export signal</term>
<term>Nuclear export signals</term>
<term>Nuclear localization</term>
<term>Nuclear localization signals</term>
<term>Nuclear proteins</term>
<term>Nucleic</term>
<term>Nucleic acids</term>
<term>Objective test</term>
<term>Other hand</term>
<term>Other sources</term>
<term>Outer membrane</term>
<term>Outer membrane proteins</term>
<term>Pathway</term>
<term>Pattern recognition algorithms</term>
<term>Peptidase</term>
<term>Peptide</term>
<term>Peroxisomal</term>
<term>Peroxisomal membrane proteins</term>
<term>Plant cell</term>
<term>Plos pathog</term>
<term>Prediction</term>
<term>Prediction accuracy</term>
<term>Prediction algorithms</term>
<term>Prediction methods</term>
<term>Prediction performance</term>
<term>Predictor</term>
<term>Presequences</term>
<term>Processing peptidase</term>
<term>Proline</term>
<term>Protein</term>
<term>Protein localization</term>
<term>Protein localization sites</term>
<term>Protein subcellular localization</term>
<term>Protein subcellular localization prediction</term>
<term>Proteome</term>
<term>Proteome analysis</term>
<term>Proteomics</term>
<term>Psort</term>
<term>Public databases</term>
<term>Recent advances</term>
<term>Receptor</term>
<term>Secretion system</term>
<term>Secretory pathway</term>
<term>Sequence homology</term>
<term>Sequence motifs</term>
<term>Sequence patterns</term>
<term>Sequence similarity</term>
<term>Serine</term>
<term>Signal peptide</term>
<term>Signal peptide cleavage site</term>
<term>Signal peptides</term>
<term>Signal region</term>
<term>Signal sequences</term>
<term>Simple method</term>
<term>Simple test</term>
<term>Single residue</term>
<term>Special interest</term>
<term>Subcellular</term>
<term>Subcellular localization</term>
<term>Subcellular localization site</term>
<term>Subcellular localization sites</term>
<term>Subcellular locations</term>
<term>Support vector machines</term>
<term>Target database</term>
<term>Test sets</term>
<term>Topology</term>
<term>Training data</term>
<term>Transit peptides</term>
<term>Transmembrane domains</term>
<term>Trends cell biol</term>
<term>Typical example</term>
<term>Verlag</term>
<term>Verlag gmbh</term>
<term>Weinheim</term>
<term>Weinheim proteomics</term>
<term>Wolf psort</term>
<term>Yeast</term>
<term>Yeast chromosome</term>
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<front><div type="abstract" xml:lang="en">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.</div>
</front>
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