HighlightsWe used a genetic algorithm (GA) in combination with C4.5 decision tree for prediction of miRNA targets.The GA-based decision tree was used for selection of the best rules out of the rule sets.We used a good measure (weighted F-measure) as fitness function.Our method extracted 7 rules, which can be implemented for other similar dataset to prediction of miRNAs target.We achieved 93.9% and 97.1% accuracy of classification for two previously published datasets.
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