Dinucleotide Step Parameterization of Pre-miRNAs Using Multi-objective Evolutionary Algorithms

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4447)


MicroRNAs (miRNAs) form a large functional family of small noncoding RNAs and play an important role as posttranscriptional regulators, by repressing the translation of mRNAs. Recently, the processing mechanism of miRNAs has been reported to involve Drosha/DGCR8 complex and Dicer, however, the exact mechanism and molecular principle are still unknown. We thus have tried to understand the related phenomena in terms of the tertiary structure of pre-miRNA. Unfortunately, the tertiary structure of RNA double helix has not been studied sufficiently compared to that of DNA double helix. The tertiary structure of pre-miRNA double helix is determined by 15 types of dinucleotide step (d-step) parameters for three classes of angles, i.e., twist, roll, and tilt. In this study, we estimate the 45 d-step parameters (15 types by 3 classes) using an evolutionary algorithm, under several assumptions inferred from the literature. Considering the trade-off among the four objective functions in our study, we deployed a multi-objective evolutionary algorithm, NSGA-II, to the search for a nondominant set of parameters. The performance of our method was evaluated on a separate test dataset. Our study provides a novel approach to understanding the processing mechanism of pre-miRNAs with respect to their tertiary structure and would be helpful for developing a comprehensible prediction method for pre-miRNA and mature miRNA structures.


Tertiary Structure Double Helix Twist Angle Decision Vector Multiobjective Evolutionary Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  1. 1.Graduate Program in Bioinformatics 
  2. 2.Center for Bioinformation Technology 
  3. 3.Biointelligence Laboratory, School of Computer Science and Engineering, Seoul National University, Seoul 151-742Korea
  4. 4.School of Computing, Soongsil University, Seoul 151-746Korea
  5. 5.Department of Computer Engineering, Kyungpook National University, Daegu 702-701Korea

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