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Bioinformatics Advance Access originally published online on June 16, 2004
Bioinformatics 2004 20(17):2928-2933; doi:10.1093/bioinformatics/bth334
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Bioinformatics vol. 20 issue 17 © Oxford University Press 2004; all rights reserved.

Mean and variance of the Gibbs free energy of oligonucleotides in the nearest neighbor model under varying conditions

Sven Rahmann 1,2,*,{dagger} and Christine Gräfe 2

1 Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, D-14195 Berlin, Germany and 2 Bioinformatics Program, Department of Mathematics and Computer Science, Freie Universität Berlin, Germany

Received on August 19, 2003; revised on March 19, 2004; accepted on May 15, 2004
Advance Access Publication June 16, 2004

Motivation: In order to assess the stability of DNA–DNA hybridizations—for example during PCR primer design or oligonucleotide selection for microarrays—one needs to predict the change in Gibbs free energy {Delta}G during hybridization. The nearest neighbor model provides a good compromise between accuracy and computational simplicity for this task.

To determine optimal combinations of reaction parameters (temperature, salt concentration, oligonucleotide length and GC-content), one would like to understand how {Delta}G depends on all of these parameters simultaneously.

Results: We derive analytic results about the distribution of nearest neighbor {Delta}G values for a Bernoulli random sequence model (specified by oligonucleotide length and average GC-content) under given experimental conditions. We find that the distribution of {Delta}G values is approximately Gaussian and provide exact formulas for expectation and variance.

Contact: Sven.Rahmann{at}cebitec.uni-bielefeld.de

* To whom correspondence should be addressed.

{dagger} Present address: Genome Informatics, Faculty of Technology, University of Bielefeld, D-33594 Bielefeld, Germany.


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