HECTAR: A method to predict subcellular targeting in heterokonts

BMC Bioinformatics

Volumn 9, Issue , 2008, Pages

  Gschloessl, Bernhard ^a,b   Guermeur, Yann ^c   Cock, J Mark ^a,b  

^a SORBONNE UNIVERSITÉ   (France)

^b CNRS   (France)

^c LORIA   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION COEFFICIENT; DIVIDE-AND-CONQUER APPROACH; EUKARYOTIC ORGANISMS; HIERARCHICAL ARCHITECTURES; SPECIFIC PROPERTIES; STATISTICAL PREDICTION; SUB-CELLULAR LOCALISATION; SUBCELLULAR TARGETING;

BIOLOGY; GENE ENCODING; PEPTIDES;

FORECASTING;

CELL PROTEIN; HETEROKONT PROTEIN; MITOCHONDRIAL PROTEIN; PEPTIDE DERIVATIVE; UNCLASSIFIED DRUG; PROTEOME;

ALGA; AMINO TERMINAL SEQUENCE; ARTICLE; CELLULAR DISTRIBUTION; CHLOROPLAST; CORRELATION COEFFICIENT; DIATOM; ENDOSYMBIOSIS; EUKARYOTE; GENE SEQUENCE; HETEROKONT; NONHUMAN; NUCLEOTIDE SEQUENCE; PHYLOGENY; PLANKTON; PREDICTION; PROTEIN LOCALIZATION; PROTEIN TARGETING; STATISTICAL ANALYSIS; SUPPORT VECTOR MACHINE; UNINDEXED SEQUENCE; ALGORITHM; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CELL FRACTIONATION; CHEMISTRY; COMPUTER PROGRAM; EUKARYOTIC CELL; METABOLISM; METHODOLOGY; SEQUENCE ANALYSIS; STRUCTURE ACTIVITY RELATION;

ALGAE; CRYPTOPHYTA; EUKARYOTA; STRAMENOPILES;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; EUKARYOTIC CELLS; PATTERN RECOGNITION, AUTOMATED; PROTEOME; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE; STRUCTURE-ACTIVITY RELATIONSHIP; SUBCELLULAR FRACTIONS;

EID: 54049114680     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-9-393     Document Type: Article

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