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• W2123015178 abstract "The assumption that DNA and RNA hybridization can be described by a two-state model, is unjustified for analysis of microarrays. It is expected that microarray analysis would benefit from a model which takes into account many different possible configurations. In this thesis, we present the tools developed to allow a many-state analysis of microarrays, and we also report many results obtained in various areas. We shall develop an algorithm to calculate many-state partition sums for DNA and RNA using an extended Nearest-neighbor model. Different incarnations of the algorithm are constructed, each of which computes the same final result, but in a separate way. Eventually, five different algorithms will be tested for their performance. The many-state model is then used to refit the literature parameters for the nearest-neighbor model. An improvement with respect to currently known values is found, even though the many-state model is not expected to be very effective at the short lengths of DNA and RNA strands that are used in the experiments reported in the literature. Two different sets of parameters are fitted and compared, and it is found that only a small subset of possible states is still present in the many-state partition sum, such that our partition sum is similar to the two-state partition sum. Finally, the many-state model is used in analysis on microarrays. In spite of problems with overfitting, a significant improvement is seen with respect to the two-state model predictions. Parameters discovered for hairpins are similar to the parameters already found in the literature. Additionally, a parameter set is derived for microarray analysis. While the limited availability of data hampers our ability to extract physically relevant parameters, the overall results indeed confirm that the many-state partition sum performs better at microarray analysis than the two-state partition sum. This leads to the conclusion that the many-state partition sum may be expected to improve DNA and RNA hybridization prediction in general. Documentation of the programs used to obtain the results in this thesis, is available as an appendix to this thesis. The source code of the programs, available under the GNU LGPL license, can be obtained from the author, or alternatively, online from http://www.math.uu.nl/people/bisseling/software.html ." @default.
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• W2123015178 date "2009-01-01" @default.
• W2123015178 modified "2023-09-27" @default.
• W2123015178 title "The many-state partition sum in DNA and RNA hybridization and its application to microarrays" @default.
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