Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments

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Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments. / Seemann, Ernst Stefan; Gorodkin, Jan; Backofen, Rolf.

In: Nucleic Acids Research, Vol. 36, No. 20, 2008, p. 6355-6362.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Seemann, ES, Gorodkin, J & Backofen, R 2008, 'Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments', Nucleic Acids Research, vol. 36, no. 20, pp. 6355-6362. https://doi.org/10.1093/nar/gkn544

APA

Seemann, E. S., Gorodkin, J., & Backofen, R. (2008). Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments. Nucleic Acids Research, 36(20), 6355-6362. https://doi.org/10.1093/nar/gkn544

Vancouver

Seemann ES, Gorodkin J, Backofen R. Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments. Nucleic Acids Research. 2008;36(20):6355-6362. https://doi.org/10.1093/nar/gkn544

Author

Seemann, Ernst Stefan ; Gorodkin, Jan ; Backofen, Rolf. / Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments. In: Nucleic Acids Research. 2008 ; Vol. 36, No. 20. pp. 6355-6362.

Bibtex

@article{68c44da0e88611ddbf70000ea68e967b,
title = "Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments",
abstract = "Computational methods for determining the secondary structure of RNA sequences from given alignments are currently either based on thermodynamic folding, compensatory base pair substitutions or both. However, there is currently no approach that combines both sources of information in a single optimization problem. Here, we present a model that formally integrates both the energy-based and evolution-based approaches to predict the folding of multiple aligned RNA sequences. We have implemented an extended version of Pfold that identifies base pairs that have high probabilities of being conserved and of being energetically favorable. The consensus structure is predicted using a maximum expected accuracy scoring scheme to smoothen the effect of incorrectly predicted base pairs. Parameter tuning revealed that the probability of base pairing has a higher impact on the RNA structure prediction than the corresponding probability of being single stranded. Furthermore, we found that structurally conserved RNA motifs are mostly supported by folding energies. Other problems (e.g. RNA-folding kinetics) may also benefit from employing the principles of the model we introduce. Our implementation, PETfold, was tested on a set of 46 well-curated Rfam families and its performance compared favorably to that of Pfold and RNAalifold.",
author = "Seemann, {Ernst Stefan} and Jan Gorodkin and Rolf Backofen",
year = "2008",
doi = "10.1093/nar/gkn544",
language = "English",
volume = "36",
pages = "6355--6362",
journal = "Nucleic Acids Research",
issn = "0305-1048",
publisher = "Oxford University Press",
number = "20",

}

RIS

TY - JOUR

T1 - Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments

AU - Seemann, Ernst Stefan

AU - Gorodkin, Jan

AU - Backofen, Rolf

PY - 2008

Y1 - 2008

N2 - Computational methods for determining the secondary structure of RNA sequences from given alignments are currently either based on thermodynamic folding, compensatory base pair substitutions or both. However, there is currently no approach that combines both sources of information in a single optimization problem. Here, we present a model that formally integrates both the energy-based and evolution-based approaches to predict the folding of multiple aligned RNA sequences. We have implemented an extended version of Pfold that identifies base pairs that have high probabilities of being conserved and of being energetically favorable. The consensus structure is predicted using a maximum expected accuracy scoring scheme to smoothen the effect of incorrectly predicted base pairs. Parameter tuning revealed that the probability of base pairing has a higher impact on the RNA structure prediction than the corresponding probability of being single stranded. Furthermore, we found that structurally conserved RNA motifs are mostly supported by folding energies. Other problems (e.g. RNA-folding kinetics) may also benefit from employing the principles of the model we introduce. Our implementation, PETfold, was tested on a set of 46 well-curated Rfam families and its performance compared favorably to that of Pfold and RNAalifold.

AB - Computational methods for determining the secondary structure of RNA sequences from given alignments are currently either based on thermodynamic folding, compensatory base pair substitutions or both. However, there is currently no approach that combines both sources of information in a single optimization problem. Here, we present a model that formally integrates both the energy-based and evolution-based approaches to predict the folding of multiple aligned RNA sequences. We have implemented an extended version of Pfold that identifies base pairs that have high probabilities of being conserved and of being energetically favorable. The consensus structure is predicted using a maximum expected accuracy scoring scheme to smoothen the effect of incorrectly predicted base pairs. Parameter tuning revealed that the probability of base pairing has a higher impact on the RNA structure prediction than the corresponding probability of being single stranded. Furthermore, we found that structurally conserved RNA motifs are mostly supported by folding energies. Other problems (e.g. RNA-folding kinetics) may also benefit from employing the principles of the model we introduce. Our implementation, PETfold, was tested on a set of 46 well-curated Rfam families and its performance compared favorably to that of Pfold and RNAalifold.

U2 - 10.1093/nar/gkn544

DO - 10.1093/nar/gkn544

M3 - Journal article

C2 - 18836192

VL - 36

SP - 6355

EP - 6362

JO - Nucleic Acids Research

JF - Nucleic Acids Research

SN - 0305-1048

IS - 20

ER -

ID: 9905593