A Machine Learning Approach for the Integration of miRNA-Target Predictions

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@InProceedings{Beretta:2016:PDP,

• author = "S. Beretta and M. Castelli and Yuliana Martinez and Luis Munoz and Sara Silva and Leonardo Trujillo and Luciano Milanesi and Ivan Merelli",
• booktitle = "2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)",
• title = "A Machine Learning Approach for the Integration of {miRNA}-Target Predictions",
• year = "2016",
• pages = "528--534",
• abstract = "Although several computational methods have been developed for predicting interactions between miRNA and target genes, there are substantial differences in the achieved results. For this reason, machine learning approaches are widely used for integrating the predictions obtained from different tools. In this work we adopt a method, called M3GP, which relies on a genetic programming approach, to classify results from three tools: miRanda, TargetScan, and RNAhybrid. Such algorithm is highly parallelisable and its adoption provides great advantages while handling problems involving big datasets, since it is independent from the implementation and from the architecture on which it is executed. More precisely, we apply this technique for the classification of the achieved miRNA target predictions and we compare its results with those obtained with other classifiers.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/PDP.2016.125",
• month = feb,
• notes = "Also known as \cite{7445385}",

}

Genetic Programming entries for Stefano Beretta Mauro Castelli Yuliana Martinez Luis Munoz Delgado Sara Silva Leonardo Trujillo Luciano Milanesi Ivan Merelli

Citations