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Eivind Tøstesen

Publications and source records attributed to Eivind Tøstesen.

3 recordsLinked to original sources

Stitchprofiles.uio.no: analysis of partly melted DNA conformations using stitch profiles.

In this study, we describe a web server that performs computations on DNA melting, thus predicting the localized separation of the two strands for sequences provided by the users. The output types are stitch profiles, melting curves, probability profiles, etc. Stitch profile diagrams visualize the ensemble of alternative conformations that DNA can adopt with different probabilities. For example, a stitch profile shows the possible loop openings in terms of their locations, sizes, probabilities and fluctuations at a given temperature. Sequences with lengths up to several tens or hundreds of kilobase pairs can be analysed. The tools are freely available at http://stitchprofiles.uio.no.

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Partly melted DNA conformations obtained with a probability peak finding method.

Peaks in the probabilities of loops or bubbles, helical segments, and unzipping ends in melting DNA are found in this article using a peak finding method that maps the hierarchical structure of certain energy landscapes. The peaks indicate the alternative conformations that coexist in equilibrium and the range of their fluctuations. This yields a representation of the conformational ensemble at a given temperature, which is illustrated in a single diagram called a stitch profile. This article describes the methodology and discusses stitch profiles vs the ordinary probability profiles using the phage lambda genome as an example.

Algorithms↗

Speed-up of DNA melting algorithm with complete nearest neighbor properties.

We describe an optimized algorithm, which is faster and more accurate compared to previously described algorithms, for computing the statistical mechanics of denaturation of nucleic acid sequences according to the classical Poland-Scheraga type of model. Nearest neighbor thermodynamics has been included in a complete and general way, by rigorously treating nearest neighbor interactions, helix end interactions, and isolated base-pairs. This avoids the simplifications of previous approaches and achieves full generality and controllability with respect to thermodynamic modeling. The algorithm computes subchain partition functions by recursion, from which various quantitative aspects of the melting process are easily derived, for example the base-pairing probability profiles. The algorithm represents an optimization with respect to algorithmic complexity of the partition function algorithm of Yeramian et al. (Biopolymers 1990, 30, 481-497): we reduce the computation time for a base-pairing probability profile from O(N2) to O(N), where N is the sequence length. This speed-up comes in addition to the speed-up due to a multiexponential approximation of the loop entropy factor as introduced by Fixman and Freire22 and applied by Yeramian et al. The speed-up, however, is independent of the multiexponential approximation and reduces time from O(N3) to O(N2) in the exact case. A method for representing very large numbers is described, which avoids numerical overflow in the partition functions for genomic length sequences. In addition to calculating the standard base-pairing probability profiles, we propose to use the algorithm to calculate various other probabilities (loops, helices, tails) for a more direct view of the melting regions and their positions and sizes. This can provide a better understanding of the physics of denaturation and the biology of genomes.

Algorithms↗