miRNA Target Prediction Based on Gene Ontology

Abstract

miRNAs have been regarded as the key regulator in post transcriptional modification involved in broad biological process. Identifying miRNA targets is one of the core challenges in studying miRNA function. Previous miRNA target prediction algorithms are mainly based on physical interaction mechanism such as sequence match and free energy. In our paper, we proposed SVM ensemble classifier based method to integrate functional information from Gene Ontology with sequence information. To supplement our method, we constructed comprehensive positive data and high quality negative data from micro-array data. Performance evaluation shows significant improvement of the proposed method in both prediction performance and the coverage of miRNA-mRNA pairs. Further analysis of the GO features used for prediction suggests they appropriately represent the functional information of miRNA target genes.