Discovering multiple realistic TFBS motifs based on a generalized model

BMC Bioinformatics

Table 2 Motif discovery methods summary.

Representations (i) Consensus (ii) Matrix and Evaluations		(a) Enumerations		(b) Stochastic Search
		Exhaustive	Non-exhaustive	Local	Global
					Single-point (Gibbs Sampling)	Multi-point (GAs)
(i)	Hamming	[7, 8]	[14]	[17, 18]		[9, 10]
	Z-score		Weeder [15, 16]			[24]
(ii)	IC		[41]		[46]	[10], GALF-P [28]
	Bayesian		BioOptimizer [40]		BioProspector [19] Motif Sampler [21]	GAME [27]
	MAP			MEME [12] MDScan [5]	AlignACE [20]

Summary of the representative motif discovery methods. The methods included in our comparison experiments are shown with their names. IC stands for Information Content.

ISSN: 1471-2105