Mean and variance of the Gibbs free energy of oligonucleotides in the nearest neighbor model under varying conditions
Author(s) -
Sven Rahmann,
Christine Gräfe
Publication year - 2004
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bth334
Subject(s) - k nearest neighbors algorithm , oligonucleotide , gaussian , bernoulli's principle , gibbs free energy , mathematics , algorithm , statistics , computer science , biological system , dna , physics , biology , artificial intelligence , thermodynamics , genetics , quantum mechanics
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 DeltaG 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 DeltaG depends on all of these parameters simultaneously.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom