Prediction of O-glycosylation sites using random forest and GA-tuned PSO technique

Bioinformatics and Biology Insights

Volumn 9, Issue , 2015, Pages 103-109

  Hassan, Hebatallah ^a   Badr, Amr ^b   Abdelhalim, M B ^a  

^a Technology and Maritime Transport   (Egypt)

^b CAIRO UNIVERSITY   (Egypt)

Author keywords

Genetic algorithm; Imbalanced learning; O glycosylation; PSO; Random forest

Indexed keywords

ACCURACY; AMINO ACID SEQUENCE; ARTICLE; CHROMOSOME; CLASSIFICATION; CLASSIFIER; GENETIC ALGORITHM; GLYCOSYLATION; O GLYCOSYLATION SITE; PARTICLE SWARM OPTIMIZATION; RANDOM FOREST; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; STATISTICAL PARAMETERS;

MAMMALIA;

EID: 84937398205     PISSN: None     EISSN: 11779322     Source Type: Journal    
DOI: 10.4137/BBI.S26864     Document Type: Article

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