Identification of consensus RNA secondary structures using suffix arrays
<p>Abstract</p> <p>Background</p> <p>The identification of a consensus RNA motif often consists in finding a conserved secondary structure with minimum free energy in an ensemble of aligned sequences. However, an alignment is often difficult to obtain without prior stru...
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doaj-8ed43c42bd6243a88f997df6219bac9a2020-11-24T21:47:47ZengBMCBMC Bioinformatics1471-21052006-05-017124410.1186/1471-2105-7-244Identification of consensus RNA secondary structures using suffix arraysNguyen TruongAnwar MohammadTurcotte Marcel<p>Abstract</p> <p>Background</p> <p>The identification of a consensus RNA motif often consists in finding a conserved secondary structure with minimum free energy in an ensemble of aligned sequences. However, an alignment is often difficult to obtain without prior structural information. Thus the need for tools to automate this process.</p> <p>Results</p> <p>We present an algorithm called Seed to identify all the conserved RNA secondary structure motifs in a set of unaligned sequences. The search space is defined as the set of all the secondary structure motifs inducible from a seed sequence. A general-to-specific search allows finding all the motifs that are conserved. Suffix arrays are used to enumerate efficiently all the biological palindromes as well as for the matching of RNA secondary structure expressions.</p> <p>We assessed the ability of this approach to uncover known structures using four datasets. The enumeration of the motifs relies only on the secondary structure definition and conservation only, therefore allowing for the independent evaluation of scoring schemes. Twelve simple objective functions based on free energy were evaluated for their potential to discriminate native folds from the rest.</p> <p>Conclusion</p> <p>Our evaluation shows that 1) support and exclusion constraints are sufficient to make an exhaustive search of the secondary structure space feasible. 2) The search space induced from a seed sequence contains known motifs. 3) Simple objective functions, consisting of a combination of the free energy of matching sequences, can generally identify motifs with high positive predictive value and sensitivity to known motifs.</p> http://www.biomedcentral.com/1471-2105/7/244 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nguyen Truong Anwar Mohammad Turcotte Marcel |
spellingShingle |
Nguyen Truong Anwar Mohammad Turcotte Marcel Identification of consensus RNA secondary structures using suffix arrays BMC Bioinformatics |
author_facet |
Nguyen Truong Anwar Mohammad Turcotte Marcel |
author_sort |
Nguyen Truong |
title |
Identification of consensus RNA secondary structures using suffix arrays |
title_short |
Identification of consensus RNA secondary structures using suffix arrays |
title_full |
Identification of consensus RNA secondary structures using suffix arrays |
title_fullStr |
Identification of consensus RNA secondary structures using suffix arrays |
title_full_unstemmed |
Identification of consensus RNA secondary structures using suffix arrays |
title_sort |
identification of consensus rna secondary structures using suffix arrays |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2006-05-01 |
description |
<p>Abstract</p> <p>Background</p> <p>The identification of a consensus RNA motif often consists in finding a conserved secondary structure with minimum free energy in an ensemble of aligned sequences. However, an alignment is often difficult to obtain without prior structural information. Thus the need for tools to automate this process.</p> <p>Results</p> <p>We present an algorithm called Seed to identify all the conserved RNA secondary structure motifs in a set of unaligned sequences. The search space is defined as the set of all the secondary structure motifs inducible from a seed sequence. A general-to-specific search allows finding all the motifs that are conserved. Suffix arrays are used to enumerate efficiently all the biological palindromes as well as for the matching of RNA secondary structure expressions.</p> <p>We assessed the ability of this approach to uncover known structures using four datasets. The enumeration of the motifs relies only on the secondary structure definition and conservation only, therefore allowing for the independent evaluation of scoring schemes. Twelve simple objective functions based on free energy were evaluated for their potential to discriminate native folds from the rest.</p> <p>Conclusion</p> <p>Our evaluation shows that 1) support and exclusion constraints are sufficient to make an exhaustive search of the secondary structure space feasible. 2) The search space induced from a seed sequence contains known motifs. 3) Simple objective functions, consisting of a combination of the free energy of matching sequences, can generally identify motifs with high positive predictive value and sensitivity to known motifs.</p> |
url |
http://www.biomedcentral.com/1471-2105/7/244 |
work_keys_str_mv |
AT nguyentruong identificationofconsensusrnasecondarystructuresusingsuffixarrays AT anwarmohammad identificationofconsensusrnasecondarystructuresusingsuffixarrays AT turcottemarcel identificationofconsensusrnasecondarystructuresusingsuffixarrays |
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