Nucleic Acids Research Advance Access originally published online on September 20, 2006
Nucleic Acids Research 2006 34(17):e117; doi:10.1093/nar/gkl544
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Nucleic Acids Research, 2006, Vol. 34, No. 17 e117
© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Using RNA secondary structures to guide sequence motif finding towards single-stranded regions
Institute of Computer Science, Chair for Bioinformatics, Albert-Ludwigs-University Freiburg Georges-Koehler-Allee 106, 79110 Freiburg, Germany
*To whom correspondence should be addressed. Tel: +49 761 203 7461; Fax: +49 761 203 7462; Email: backofen{at}informatik.uni-freiburg.de
Received May 30, 2006. Revised July 7, 2006. Accepted July 13, 2006.
RNA binding proteins recognize RNA targets in a sequence specific manner. Apart from the sequence, the secondary structure context of the binding site also affects the binding affinity. Binding sites are often located in single-stranded RNA regions and it was shown that the sequestration of a binding motif in a double-strand abolishes protein binding. Thus, it is desirable to include knowledge about RNA secondary structures when searching for the binding motif of a protein. We present the approach MEMERIS for searching sequence motifs in a set of RNA sequences and simultaneously integrating information about secondary structures. To abstract from specific structural elements, we precompute position-specific values measuring the single-strandedness of all substrings of an RNA sequence. These values are used as prior knowledge about the motif starts to guide the motif search. Extensive tests with artificial and biological data demonstrate that MEMERIS is able to identify motifs in single-stranded regions even if a stronger motif located in double-strand parts exists. The discovered motif occurrences in biological datasets mostly coincide with known protein-binding sites. This algorithm can be used for finding the binding motif of single-stranded RNA-binding proteins in SELEX or other biological sequence data.
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