Accurate microRNA Target Prediction Using Detailed Binding Site Accessibility and Machine Learning on Proteomics Data

@article{Reczko2012AccurateMT,
  title={Accurate microRNA Target Prediction Using Detailed Binding Site Accessibility and Machine Learning on Proteomics Data},
  author={M. Reczko and Manolis Maragkakis and P. Alexiou and G. Papadopoulos and A. Hatzigeorgiou},
  journal={Frontiers in Genetics},
  year={2012},
  volume={2}
}
  • M. Reczko, Manolis Maragkakis, +2 authors A. Hatzigeorgiou
  • Published 2012
  • Biology, Medicine
  • Frontiers in Genetics
  • MicroRNAs (miRNAs) are a class of small regulatory genes regulating gene expression by targeting messenger RNA. Though computational methods for miRNA target prediction are the prevailing means to analyze their function, they still miss a large fraction of the targeted genes and additionally predict a large number of false positives. Here we introduce a novel algorithm called DIANA-microT-ANN which combines multiple novel target site features through an artificial neural network (ANN) and is… CONTINUE READING
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