RNA secondary structure prediction using a self-consistent mean field approach.
Standard
RNA secondary structure prediction using a self-consistent mean field approach. / Kleesiek, Jens; Torda, Andrew E.
in: J COMPUT CHEM, 2009.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
Harvard
APA
Vancouver
Bibtex
}
RIS
TY - JOUR
T1 - RNA secondary structure prediction using a self-consistent mean field approach.
AU - Kleesiek, Jens
AU - Torda, Andrew E
PY - 2009
Y1 - 2009
N2 - We propose a method for predicting RNA base pairing which imposes no restrictions on the order of base pairs, allows for pseudoknots and runs in O(mN(2)) time for N base pairs and m iterations. It employs a self-consistent mean field method in which all base pairs are possible, but with each iteration, the most energetically favored base pairs become more likely as long as they are consistent with their neighbors. Performance was compared against three other programs using three test sets. Sensitivity varied from 20% to 74% and specificity from 44% to 77% and generally, the method predicts too many base pairs leading to good sensitivity and worse specificity. The predicted structures have excellent energies suggesting that, algorithmically, the method performs well, but the classic literature energy models may not be appropriate when pseudoknots are permitted. Website and source code for the simulations are available at http://cardigan.zbh.uni-hamburg.de/ approximately rnascmf. (c) 2009 Wiley Periodicals, Inc. J Comput Chem, 2010.
AB - We propose a method for predicting RNA base pairing which imposes no restrictions on the order of base pairs, allows for pseudoknots and runs in O(mN(2)) time for N base pairs and m iterations. It employs a self-consistent mean field method in which all base pairs are possible, but with each iteration, the most energetically favored base pairs become more likely as long as they are consistent with their neighbors. Performance was compared against three other programs using three test sets. Sensitivity varied from 20% to 74% and specificity from 44% to 77% and generally, the method predicts too many base pairs leading to good sensitivity and worse specificity. The predicted structures have excellent energies suggesting that, algorithmically, the method performs well, but the classic literature energy models may not be appropriate when pseudoknots are permitted. Website and source code for the simulations are available at http://cardigan.zbh.uni-hamburg.de/ approximately rnascmf. (c) 2009 Wiley Periodicals, Inc. J Comput Chem, 2010.
M3 - SCORING: Zeitschriftenaufsatz
JO - J COMPUT CHEM
JF - J COMPUT CHEM
SN - 0192-8651
ER -
