1. GibbsSampler
2. GibbsSamplerOrdinary

GibbsSampler using Bayesian Inference

Sequences MotifLength iterT: iteriate times, the higher, the more accurate, the slower CtrlN: Whether or not use strategy 1, set 0 means DO NOT apply strategy 1, set -1 means apply strategy 1, but the real value of CtrlN is given by program automaticall set a positive number as real value of CtrlN, notice that it must be less than iterT improve: Whether or not use strategy 2 set false means DO NOT apply strategy 2 set true means apply strategy 2 alpha: DO NOT recommend that set it by yourself beta: DO NOT recommend that set it by yourself

Motifs = GibbsSampler(Sequences, 10, 3000, 0, true)

MotifLength = 10, iterT=3000, CtrlN=0 means DO NOT apply strategy 1, improve = true means apply strategy 2

Motifs = GibbsSampler(Sequences, 12, 5000, -1, false)

MotifLength = 12, iterT=5000, CtrlN=-1 means apply strategy 1 but the real value is given by program, improve = flase means DO NOT apply strategy 2

Orindar GibbsSampler method

Sequences MotifLength iterT: iteriate times, the higher, the more accurate, the slower

Motifs, score, _, _ = GibbsSamplerOrdinary(Sequences, 10, 10000)

MotifLength = 10, iterT=10000,