Free energy estimation of short DNA duplex hybridizations

<p>Abstract</p> <p>Background</p> <p>Estimation of DNA duplex hybridization free energy is widely used for predicting cross-hybridizations in DNA computing and microarray experiments. A number of software programs based on different methods and parametrizations are avai...

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Main Authors: Leger Serge, Andronescu Mirela, Tulpan Dan
Format: Article
Language:English
Published: BMC 2010-02-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/11/105
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spelling doaj-40aeb2c8818c4857aa3e291543802c272020-11-25T01:05:28ZengBMCBMC Bioinformatics1471-21052010-02-0111110510.1186/1471-2105-11-105Free energy estimation of short DNA duplex hybridizationsLeger SergeAndronescu MirelaTulpan Dan<p>Abstract</p> <p>Background</p> <p>Estimation of DNA duplex hybridization free energy is widely used for predicting cross-hybridizations in DNA computing and microarray experiments. A number of software programs based on different methods and parametrizations are available for the theoretical estimation of duplex free energies. However, significant differences in free energy values are sometimes observed among estimations obtained with various methods, thus being difficult to decide what value is the accurate one.</p> <p>Results</p> <p>We present in this study a quantitative comparison of the similarities and differences among four published DNA/DNA duplex free energy calculation methods and an extended Nearest-Neighbour Model for perfect matches based on triplet interactions. The comparison was performed on a benchmark data set with 695 pairs of short oligos that we collected and manually curated from 29 publications. Sequence lengths range from 4 to 30 nucleotides and span a large GC-content percentage range. For perfect matches, we propose an extension of the Nearest-Neighbour Model that matches or exceeds the performance of the existing ones, both in terms of correlations and root mean squared errors. The proposed model was trained on experimental data with temperature, sodium and sequence concentration characteristics that span a wide range of values, thus conferring the model a higher power of generalization when used for free energy estimations of DNA duplexes under non-standard experimental conditions.</p> <p>Conclusions</p> <p>Based on our preliminary results, we conclude that no statistically significant differences exist among free energy approximations obtained with 4 publicly available and widely used programs, when benchmarked against a collection of 695 pairs of short oligos collected and curated by the authors of this work based on 29 publications. The extended Nearest-Neighbour Model based on triplet interactions presented in this work is capable of performing accurate estimations of free energies for perfect match duplexes under both standard and non-standard experimental conditions and may serve as a baseline for further developments in this area of research.</p> http://www.biomedcentral.com/1471-2105/11/105
collection DOAJ
language English
format Article
sources DOAJ
author Leger Serge
Andronescu Mirela
Tulpan Dan
spellingShingle Leger Serge
Andronescu Mirela
Tulpan Dan
Free energy estimation of short DNA duplex hybridizations
BMC Bioinformatics
author_facet Leger Serge
Andronescu Mirela
Tulpan Dan
author_sort Leger Serge
title Free energy estimation of short DNA duplex hybridizations
title_short Free energy estimation of short DNA duplex hybridizations
title_full Free energy estimation of short DNA duplex hybridizations
title_fullStr Free energy estimation of short DNA duplex hybridizations
title_full_unstemmed Free energy estimation of short DNA duplex hybridizations
title_sort free energy estimation of short dna duplex hybridizations
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2010-02-01
description <p>Abstract</p> <p>Background</p> <p>Estimation of DNA duplex hybridization free energy is widely used for predicting cross-hybridizations in DNA computing and microarray experiments. A number of software programs based on different methods and parametrizations are available for the theoretical estimation of duplex free energies. However, significant differences in free energy values are sometimes observed among estimations obtained with various methods, thus being difficult to decide what value is the accurate one.</p> <p>Results</p> <p>We present in this study a quantitative comparison of the similarities and differences among four published DNA/DNA duplex free energy calculation methods and an extended Nearest-Neighbour Model for perfect matches based on triplet interactions. The comparison was performed on a benchmark data set with 695 pairs of short oligos that we collected and manually curated from 29 publications. Sequence lengths range from 4 to 30 nucleotides and span a large GC-content percentage range. For perfect matches, we propose an extension of the Nearest-Neighbour Model that matches or exceeds the performance of the existing ones, both in terms of correlations and root mean squared errors. The proposed model was trained on experimental data with temperature, sodium and sequence concentration characteristics that span a wide range of values, thus conferring the model a higher power of generalization when used for free energy estimations of DNA duplexes under non-standard experimental conditions.</p> <p>Conclusions</p> <p>Based on our preliminary results, we conclude that no statistically significant differences exist among free energy approximations obtained with 4 publicly available and widely used programs, when benchmarked against a collection of 695 pairs of short oligos collected and curated by the authors of this work based on 29 publications. The extended Nearest-Neighbour Model based on triplet interactions presented in this work is capable of performing accurate estimations of free energies for perfect match duplexes under both standard and non-standard experimental conditions and may serve as a baseline for further developments in this area of research.</p>
url http://www.biomedcentral.com/1471-2105/11/105
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