Intragenomic reiterations detection using hidden Markov models
Identifieur interne : 008967 ( Main/Merge ); précédent : 008966; suivant : 008968Intragenomic reiterations detection using hidden Markov models
Auteurs : Sébastien Hergalant ; Bertrand Aigle ; Bernard Decaris ; Pierre Leblond ; Jean-François MariSource :
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Abstract
We present a genomic data mining method in which the user describes a signal worked out by a second order HMM. This signal representing the probability to classify a nucleotidic residue or a group of residues in a particular state, allows the localization of repetitions in a complete bacterial genomic sequence.
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<author><name sortKey="Aigle, Bertrand" sort="Aigle, Bertrand" uniqKey="Aigle B" first="Bertrand" last="Aigle">Bertrand Aigle</name>
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<author><name sortKey="Decaris, Bernard" sort="Decaris, Bernard" uniqKey="Decaris B" first="Bernard" last="Decaris">Bernard Decaris</name>
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<author><name sortKey="Leblond, Pierre" sort="Leblond, Pierre" uniqKey="Leblond P" first="Pierre" last="Leblond">Pierre Leblond</name>
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<author><name sortKey="Mari, Jean Francois" sort="Mari, Jean Francois" uniqKey="Mari J" first="Jean-François" last="Mari">Jean-François Mari</name>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>bacterial genomes</term>
<term>hmm</term>
<term>repeats</term>
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<front><div type="abstract" xml:lang="en" wicri:score="814">We present a genomic data mining method in which the user describes a signal worked out by a second order HMM. This signal representing the probability to classify a nucleotidic residue or a group of residues in a particular state, allows the localization of repetitions in a complete bacterial genomic sequence.</div>
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