Prediction of microRNA targets in Caenorhabditis elegans using a self-organizing map

• Published in: Bioinformatics Vol. 27; no. 9; pp. 1247 - 1254
• Main Authors: Heikkinen, Liisa, Kolehmainen, Mikko, Wong, Garry
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 01.05.2011
• Subjects: Algorithms; Animals; Artificial Intelligence; Binding Sites; Biological and medical sciences; Caenorhabditis elegans; Caenorhabditis elegans - genetics; Caenorhabditis elegans - metabolism; Cluster Analysis; Computational Biology - methods; Fundamental and applied biological sciences. Psychology; General aspects; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); MicroRNAs - genetics; MicroRNAs - metabolism; RNA, Helminth - genetics; RNA, Helminth - metabolism; Software; Caenorhabditis elegans; Target; Self organization; Prediction; Helmintha; Nemathelminthia; Invertebrata; Nematoda
• ISSN: 1367-4803; 1367-4811; 1367-4811; 1460-2059
• DOI: 10.1093/bioinformatics/btr144

Motivation: MicroRNAs (miRNAs) are small non-coding RNAs that regulate transcriptional processes via binding to the target gene mRNA. In animals, this binding is imperfect, which makes the computational prediction of animal miRNA targets a challenging task. The accuracy of miRNA target prediction can be improved with the use of machine learning methods. Previous work has described methods using supervised learning, but they suffer from the lack of adequate training examples, a common problem in miRNA target identification, which often leads to deficient generalization ability. Results: In this work, we introduce mirSOM, a miRNA target prediction tool based on clustering of short 3′-untranslated region (3′-UTR) substrings with self-organizing map (SOM). As our method uses unsupervised learning and a large set of verified Caenorhabditis elegans 3′-UTRs, we did not need to resort to training using a known set of targets. Our method outperforms seven other methods in predicting the experimentally verified C.elegans true and false miRNA targets. Availability: mirSOM miRNA target predictions are available at http://kokki.uku.fi/bioinformatics/mirsom. Contact:  liisa.heikkinen@uef.fi Supplementary information:  Supplementary data are available at Bioinformatics online.