scholarly journals A sensitivity analysis of RNA folding nearest neighbor parameters identifies a subset of free energy parameters with the greatest impact on RNA secondary structure prediction

2017 ◽  
Vol 45 (10) ◽  
pp. 6168-6176 ◽  
Author(s):  
Jeffrey Zuber ◽  
Hongying Sun ◽  
Xiaoju Zhang ◽  
Iain McFadyen ◽  
David H. Mathews
Keyword(s):  
Sensitivity Analysis ◽  
Free Energy ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Rna Secondary Structure ◽  
Nearest Neighbor ◽  
Rna Folding ◽  
Secondary Structure Prediction ◽  
Rna Secondary Structure Prediction ◽  
Energy Parameters

scholarly journals An efficient simulated annealing algorithm for the RNA secondary structure prediction with Pseudoknots

BMC Genomics ◽  
2019 ◽  
Vol 20 (S13) ◽  
Author(s):  
Zhang Kai ◽  
Wang Yuting ◽  
Lv Yulin ◽  
Liu Jun ◽  
He Juanjuan
Keyword(s):  
Free Energy ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Rna Secondary Structure ◽  
Simulated Annealing Algorithm ◽  
Secondary Structure Prediction ◽  
Stem Length ◽  
Base Pairs ◽  
Rna Secondary Structure Prediction ◽  
Prediction Algorithms

Abstract Background RNA pseudoknot structures play an important role in biological processes. However, existing RNA secondary structure prediction algorithms cannot predict the pseudoknot structure efficiently. Although random matching can improve the number of base pairs, these non-consecutive base pairs cannot make contributions to reduce the free energy. Result In order to improve the efficiency of searching procedure, our algorithm take consecutive base pairs as the basic components. Firstly, our algorithm calculates and archive all the consecutive base pairs in triplet data structure, if the number of consecutive base pairs is greater than given minimum stem length. Secondly, the annealing schedule is adapted to select the optimal solution that has minimum free energy. Finally, the proposed algorithm is evaluated with the real instances in PseudoBase. Conclusion The experimental results have been demonstrated to provide a competitive and oftentimes better performance when compared against some chosen state-of-the-art RNA structure prediction algorithms.

scholarly journals An Improved Algorithm for RNA Secondary Structure Prediction

1999 ◽  
Vol 6 (15) ◽  
Author(s):  
Rune B. Lyngsø ◽  
Michael Zuker ◽  
Christian N. S. Pedersen
Keyword(s):  
Free Energy ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Rna Secondary Structure ◽  
Secondary Structure Prediction ◽  
Biological Processes ◽  
Loop Formation ◽  
Rna Secondary Structure Prediction ◽  
Rna Molecules ◽  
Equilibrium Partition

Though not as abundant in known biological processes as proteins,<br />RNA molecules serve as more than mere intermediaries between<br />DNA and proteins, e.g. as catalytic molecules. Furthermore,<br />RNA secondary structure prediction based on free energy<br />rules for stacking and loop formation remains one of the few major<br />breakthroughs in the field of structure prediction. We present a<br />new method to evaluate all possible internal loops of size at most<br />k in an RNA sequence, s, in time O(k|s|^2); this is an improvement<br />from the previously used method that uses time O(k^2|s|^2).<br />For unlimited loop size this improves the overall complexity of<br />evaluating RNA secondary structures from O(|s|^4) to O(|s|^3) and<br />the method applies equally well to finding the optimal structure<br />and calculating the equilibrium partition function. We use our<br />method to examine the soundness of setting k = 30, a commonly<br />used heuristic.

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