Table 1 Overview of methods. The match model is the consensus representation of a single motif, motif combination is how the component scores of a composite motif are combined, and distance score is how the conservation of inter-motif distances within a composite motif is modeled.

Weeder [42]

mismatch

-

-

Dyad analysis [35]

oligos

dyad¹

constraint

MCAST [71]

PWM

sum

gap penalty

REDUCE [67]

PWM

dyad

constraint²

MDScan [87]

PWM

-

-

Gibbs sampler [97]

PWM

intersection³

uniform

MEME [98]

PWM

-

-

LOGOS [73]

DM

HMM

distribution

Motif regressor [89]

PWM

-

-

ModuleSearcher [70]

PWM

sum

window⁴

Stubb [48]

PWM

HMM

window

GANN [60]

flexible

ANN⁵

window

ANN-Spec [86]

PWM

-

-

(Wasserman) [58]

PWM

Logistic regr.

window

CoBind [68]

PWM

sum

window

Cister [72]

PWM

HMM

distribution

SeSiMCMC [122]

PWM

-

-

SMILE [40, 123]

mismatch

intersection

constraint

BioProspector [49]

PWM

sum

constraint

(Segal) [94]

PWM

-

-

(Sinha) [33]

reg.exp

dyad

constraint

ConsecID [56]

PWM

intersection

window

SCORE [69]

IUPAC

intersection

window

Gibbs recursive [52]

PWM

mixture model

distribution

(Hong) [95]

PWM

-

-

AlignACE [124]

PWM

-

-

Improbizer [117]

PWM

-

-

CisModule [119]

PWM

mixture model

mixture model

(Thompson) [66]

PWM

Markov model

constraint