Machine learning method for knowledge discovery experimented with otoneurological data
Computer Methods and Programs in Biomedicine
Computational Biology and Chemistry
MicroRNAs and cancer-the search begins!
IEEE Transactions on Information Technology in Biomedicine
PMirP: A pre-microRNA prediction method based on structure-sequence hybrid features
Artificial Intelligence in Medicine
In silico prediction of noncoding RNAs using supervised learning and feature ranking methods
International Journal of Bioinformatics Research and Applications
In silico prediction of noncoding RNAs using supervised learning and feature ranking methods
International Journal of Bioinformatics Research and Applications
Prediction of pre-miRNA with multiple stem-loops using pruning algorithm
Computers in Biology and Medicine
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Motivation: Most computational methodologies for microRNA gene prediction utilize techniques based on sequence conservation and/or structural similarity. In this study we describe a new technique, which is applicable across several species, for predicting miRNA genes. This technique is based on machine learning, using the Naïve Bayes classifier. It automatically generates a model from the training data, which consists of sequence and structure information of known miRNAs from a variety of species. Results: Our study shows that the application of machine learning techniques, along with the integration of data from multiple species is a useful and general approach for miRNA gene prediction. Based on our experiments, we believe that this new technique is applicable to an extensive range of eukaryotes' genomes. Specific structure and sequence features are first used to identify miRNAs followed by a comparative analysis to decrease the number of false positives (FPs). The resulting algorithm exhibits higher specificity and similar sensitivity compared to currently used algorithms that rely on conserved genomic regions to decrease the rate of FPs. Availability: The BayesMiRNAfind program is available at http://wotan.wistar.upenn.edu/miRNA Contact: showe@wistar.org Supplementary information: Supplementary data are available at Bioinformatics online.