Sublinear Time Motif Discovery from Multiple Sequences
نویسندگان
چکیده
منابع مشابه
Sublinear Time Motif Discovery from Multiple Sequences
In this paper, a natural probabilistic model for motif discovery has been used to experimentally test the quality of motif discovery programs. In this model, there are k background sequences, and each character in a background sequence is a random character from an alphabet, Σ. A motif G = g1g2 . . . gm is a string of m characters. In each background sequence is implanted a probabilistically-ge...
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We study a natural probabilistic model for motif discovery that has been used to experimentally test the quality of motif discovery programs. In this model, there are k background sequences, and each character in a background sequence is a random character from an alphabet Σ. A motif G = g1g2 . . . gm is a string of m characters. Each background sequence is implanted a randomly generated approx...
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We study a natural probabilistic model for motif discovery that has been used to experimentally test the quality of motif discovery programs. In this model, there are k background sequences, and each character in a background sequence is a random character from an alphabet Σ. A motif G = g1g2 · · · gm is a string of m characters. Each background sequence is implanted into a probabilistically ge...
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MOTIVATION This paper studies the problem of discovering subsequences, known as motifs, that are common to a given collection of related biosequences, by proposing a greedy algorithm for learning a mixture of motifs model through likelihood maximization. The approach adds sequentially a new motif to a mixture model by performing a combined scheme of global and local search for appropriately ini...
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ژورنال
عنوان ژورنال: Algorithms
سال: 2013
ISSN: 1999-4893
DOI: 10.3390/a6040636