Literature DB >> 12926009

A partition function algorithm for nucleic acid secondary structure including pseudoknots.

Robert M Dirks1, Niles A Pierce.   

Abstract

Nucleic acid secondary structure models usually exclude pseudoknots due to the difficulty of treating these nonnested structures efficiently in structure prediction and partition function algorithms. Here, the standard secondary structure energy model is extended to include the most physically relevant pseudoknots. We describe an O(N(5)) dynamic programming algorithm, where N is the length of the strand, for computing the partition function and minimum energy structure over this class of secondary structures. Hence, it is possible to determine the probability of sampling the lowest energy structure, or any other structure of particular interest. This capability motivates the use of the partition function for the design of DNA or RNA molecules for bioengineering applications. Copyright 2003 Wiley Periodicals, Inc.

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Year:  2003        PMID: 12926009     DOI: 10.1002/jcc.10296

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  101 in total

1.  Using an RNA secondary structure partition function to determine confidence in base pairs predicted by free energy minimization.

Authors:  David H Mathews
Journal:  RNA       Date:  2004-08       Impact factor: 4.942

2.  Paradigms for computational nucleic acid design.

Authors:  Robert M Dirks; Milo Lin; Erik Winfree; Niles A Pierce
Journal:  Nucleic Acids Res       Date:  2004-02-27       Impact factor: 16.971

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4.  Evaluation of a sophisticated SCFG design for RNA secondary structure prediction.

Authors:  Markus E Nebel; Anika Scheid
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5.  On the page number of RNA secondary structures with pseudoknots.

Authors:  Peter Clote; Stefan Dobrev; Ivan Dotu; Evangelos Kranakis; Danny Krizanc; Jorge Urrutia
Journal:  J Math Biol       Date:  2011-12-10       Impact factor: 2.259

6.  TurboKnot: rapid prediction of conserved RNA secondary structures including pseudoknots.

Authors:  Matthew G Seetin; David H Mathews
Journal:  Bioinformatics       Date:  2012-01-27       Impact factor: 6.937

7.  A domain-based model for predicting large and complex pseudoknotted structures.

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Journal:  RNA Biol       Date:  2012-02-01       Impact factor: 4.652

8.  ProbKnot: fast prediction of RNA secondary structure including pseudoknots.

Authors:  Stanislav Bellaousov; David H Mathews
Journal:  RNA       Date:  2010-08-10       Impact factor: 4.942

9.  Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles.

Authors:  Benjamin D Allen; Alex Nisthal; Stephen L Mayo
Journal:  Proc Natl Acad Sci U S A       Date:  2010-11-02       Impact factor: 11.205

10.  Heuristic RNA pseudoknot prediction including intramolecular kissing hairpins.

Authors:  Jana Sperschneider; Amitava Datta; Michael J Wise
Journal:  RNA       Date:  2010-11-22       Impact factor: 4.942

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