Literature DB >> 18830596

Watson-Crick pairing, the Heisenberg group and Milnor invariants.

Siddhartha Gadgil1.   

Abstract

We study the secondary structure of RNA determined by Watson-Crick pairing without pseudo-knots using Milnor invariants of links. We focus on the first non-trivial invariant, which we call the Heisenberg invariant. The Heisenberg invariant, which is an integer, can be interpreted in terms of the Heisenberg group as well as in terms of lattice paths. We show that the Heisenberg invariant gives a lower bound on the number of unpaired bases in an RNA secondary structure. We also show that the Heisenberg invariant can predict allosteric structures for RNA. Namely, if the Heisenberg invariant is large, then there are widely separated local maxima (i.e., allosteric structures) for the number of Watson-Crick pairs found.

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Year:  2008        PMID: 18830596     DOI: 10.1007/s00285-008-0223-x

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  14 in total

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Authors:  B Knudsen; J Hein
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Review 5.  How RNA folds.

Authors:  I Tinoco; C Bustamante
Journal:  J Mol Biol       Date:  1999-10-22       Impact factor: 5.469

6.  A statistical sampling algorithm for RNA secondary structure prediction.

Authors:  Ye Ding; Charles E Lawrence
Journal:  Nucleic Acids Res       Date:  2003-12-15       Impact factor: 16.971

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

Authors:  Robert M Dirks; Niles A Pierce
Journal:  J Comput Chem       Date:  2003-10       Impact factor: 3.376

8.  Alignment of RNA base pairing probability matrices.

Authors:  Ivo L Hofacker; Stephan H F Bernhart; Peter F Stadler
Journal:  Bioinformatics       Date:  2004-04-08       Impact factor: 6.937

Review 9.  Relics from the RNA world.

Authors:  D C Jeffares; A M Poole; D Penny
Journal:  J Mol Evol       Date:  1998-01       Impact factor: 2.395

10.  A comprehensive comparison of comparative RNA structure prediction approaches.

Authors:  Paul P Gardner; Robert Giegerich
Journal:  BMC Bioinformatics       Date:  2004-09-30       Impact factor: 3.169

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