SPRED: A machine learning approach for the identification of classical and non-classical secretory proteins in mammalian genomes

Biochemical and Biophysical Research Communications

Volumn 391, Issue 3, 2010, Pages 1306-1311

  Kandaswamy, Krishna Kumar ^a   Pugalenthi, Ganesan ^b   Hartmann, Enno ^a   Kalies, Kai Uwe ^a   Möller, Steffen ^a   Suganthan, P N ^b   Martinetz, Thomas ^a  

^a UNIVERSITY OF LÜBECK   (Germany)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Classical pathway; Human proteome; Non classical pathway; Random forest; Secretory proteins; Signal peptide

Indexed keywords

ACIDIC FIBROBLAST GROWTH FACTOR; BASIC FIBROBLAST GROWTH FACTOR; CALRETICULIN; CALVASCULIN; CILIARY NEUROTROPHIC FACTOR; CYTOPLASM PROTEIN; GALECTIN 1; GALECTIN 3; GLUTATHIONE TRANSFERASE P1; HIGH MOBILITY GROUP PROTEIN; HIGH MOBILITY GROUP PROTEIN B1; HISTONE H4; HOMEOBOX PROTEIN ENGRAILED 2; HOMEODOMAIN PROTEIN; INTERLEUKIN 18; INTERLEUKIN 1ALPHA; INTERLEUKIN 1BETA; MACROPHAGE MIGRATION INHIBITION FACTOR; NUCLEAR PROTEIN; PEROXIREDOXIN 1; PROTEIN S 100; PROTEIN S100 A2; PROTEOME; SECRETORY PROTEIN; THIOREDOXIN; THIOSULFATE SULFURTRANSFERASE; UNCLASSIFIED DRUG;

ACCURACY; AMINO ACID SEQUENCE; AMINO TERMINAL SEQUENCE; ARTICLE; COMPUTER PROGRAM; HUMAN; MACHINE LEARNING; NONHUMAN; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN SECRETION; SENSITIVITY AND SPECIFICITY; SIGNAL TRANSDUCTION;

ANIMALS; ARTIFICIAL INTELLIGENCE; GENOME, HUMAN; HUMANS; PROTEINS; PROTEOME; SEQUENCE ANALYSIS, PROTEIN;

EUKARYOTA; MAMMALIA;

EID: 73949133327     PISSN: 0006291X     EISSN: 10902104     Source Type: Journal    
DOI: 10.1016/j.bbrc.2009.12.019     Document Type: Article

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