Lecture_4_motifs

5 choose a new star0ng posi0on for the removed

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Unformatted text preview: e star0ng posi0ons randomly, there is liYle chance that our guess will be close to an op0mal mo0f, meaning it will take a very long 0me to find the op0mal mo0f. •  It is unlikely that the random star0ng posi0ons will lead us to the correct solu0on at all. •  In prac0ce, this algorithm is run many 0mes with the hope that random star0ng posi0ons will be close to the op0mum solu0on simply by chance. •  The greedy profile mo0f search algorithm is probably not the best way to find mo0fs •  However, we can improve the algorithm by introducing Gibbs Sampling, an itera0ve procedure that discards one L- mer aher each itera0on and replaces it with a new one. •  Gibbs Sampling proceeds more slowly and chooses new L- mers at random increasing the odds that it will converge to the c...
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