Titlebook: Comparative Gene Finding; Models, Algorithms a Marina Axelson-Fisk Book 20101st edition Springer-Verlag London 2010 Bioinformatics.Biologic

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Implementation of a Comparative Gene Finder, finder particularly adapted to eukaryotes, and works by simultaneously aligning and annotating two homologous sequences. The basic framework of SLAM is a generalized pair hidden Markov model, which is a seamless merging of pair hidden Markov models typically used for pairwise alignments, and genera

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Signal Processing and Information Technologyxity. As a result, a flora of heuristic alignment algorithms have evolved. In the second part of the chapter we give an account of the most common of these models, including progressive alignments, iterative methods, hidden Markov models, genetic algorithms, simulated annealing, and alignment profiles.

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https://doi.org/10.1007/978-3-319-45372-9, to pair hidden Markov models and generalized pair hidden Markov models, to gene mapping. Last we present some of the first attempts to extend the pairwise approaches to multiple sequence gene finding. Each section is finished off by an example of a gene finding software using the method in question.

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Markov Model and Hidden Stochastic Modelof a candidate exon or intron. In this chapter we describe some of the main submodels used in gene finding algorithms, and detail a number of different methods for integrating the sensors the submodels incorporate.

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