Interdisciplinary Bio Central
Etc. (Bioinformatics/Computational biology/Molecular modeling)

Prediction of RNA structures containing pseudoknots
Dongkyu Lee1,2 and Kyungsook Han1,*
1School of Computer Science and Engineering, Inha University, Inchon, Korea
2Current address: Korea Institute of Science and Technology, Seoul, Korea
*Corresponding author
  Published : February 28, 2006
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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This paper describes a genetic algorithm for predicting RNA structures that contain various types of pseudoknots. Pseudoknotted RNA structures are much more difficult to predict by computational methods than RNA secondary structures, as they are more complex and the analysis is time-consuming. We developed an efficient genetic algorithm to predict RNA folding structures containing any type of pseudoknot, as well as a novel initial population method to decrease computational complexity and increase the accuracy of the results. We also used an interaction filter to decrease the size of the possible stem lists for long RNA sequences. We predicted RNA structures using a number of different termination conditions and compared the validity of the results and the times required for the analyses. The algorithm proved able to predict efficiently RNA structures containing various types of pseudoknots.

Keyword: RNA structure, pseudoknots
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