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View all- Fu BFu YXue Y(2013)Sublinear Time Motif Discovery from Multiple SequencesAlgorithms10.3390/a60406366:4(636-677)Online publication date: 14-Oct-2013
Discovering almost any hidden motif from multiple sequences
Authors: 
Bin Fu, Ming-Yang Kao, Lusheng WangAuthors Info & Claims
Bin Fu, Ming-Yang Kao, Lusheng WangAuthors Info & ClaimsArticle No.: 26, Pages 1 - 18
Abstract
We study a natural probabilistic model for motif discovery. 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 with a probabilistically generated approximate copy of G. For a probabilistically generated approximate copy b1b2… bm of G, every character is probabilistically generated such that the probability for bi≠ gi is at most α.
In this article, we develop an efficient algorithm that can discover a hidden motif from a set of sequences for any alphabet Σ with |Σ|≥ 2 and is applicable to DNA motif discovery. We prove that for α < 1/8(1- 1/|Σ|), there exist positive constants c0, ϵ, and δ2 such that if there are at least c0 log n input sequences, then in O(n2/h(log n)O(1)) time this algorithm finds the motif with probability at least 3/4 for every G∈ Σρ-Ψρ, h,ϵ(Σ), where n the length of longest sequences, ρ is the length of the motif, h is a parameter with ρ≥ 4h≥ δ2log n, and Ψρ, h,ϵ(Σ) is a small subset of at most 2−Θ(ϵ2 h) fraction of the sequences in Σρ.
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Publication History
Published: 31 March 2011
Accepted: 01 February 2010
Revised: 01 February 2010
Received: 01 April 2008
Published in TALG Volume 7, Issue 2
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View all- Fu BFu YXue Y(2013)Sublinear Time Motif Discovery from Multiple SequencesAlgorithms10.3390/a60406366:4(636-677)Online publication date: 14-Oct-2013
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