Publication details

Brona Brejova, Daniel G. Brown, Tomas Vinar. Optimal DNA signal recognition models with a fixed amount of intrasignal dependency. In G. Benson, R. Page, ed., Algorithms and Bioinformatics: 3rd International Workshop (WABI), 2812 volume of Lecture Notes in Bioinformatics, pp. 78-94, Budapest, Hungary, September 2003. Springer.
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We study new probabilistic models for signals in DNA. Our models allow
dependencies between multiple non-adjacent positions, in a generative
model we call a higher-order tree. Computing the model of maximum
likelihood is equivalent in our context to computing a minimum
directed spanning hypergraph, a problem we show is NP-complete. We
instead compute good models using simple greedy heuristics. In
practice, the advantage of using our models over more standard models
based on adjacent positions is modest. However, there is a notable
improvement in the estimation of the probability that a given position
is a signal, which is useful in the context of probabilistic gene
finding. We also show that there is little improvement by
incorporating multiple signals involved in gene structure into a
composite signal model in our framework, though again this gives
better estimation of the probability that a site is an acceptor site



Mailing address:
Bronislava Brejova
Katedra informatiky
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