To solve (4), current algorithms begin at random initial alignment positions and attempt to converge to an alignment of l - mers in all of the sequences that maximize the objective function. In other words, the l - mer whose log(A)i is the highest (with a given PSSM) is noted in every sequence as part of the current alignment. During the maximization of A(Q) function, the probability weight matrix and hence the corresponding alignments of l - mers are updated. This occurs iteratively until the PSSM converges to the local optimal solution. The consensus pattern is obtained from the nucleotide with the largest weight in each position (column) of the PSSM. This converged PSSM and the set of alignments correspond to a local optimal solution. The exit phase where the neighborhood of the original solution is explored in a systematic manner is shown below: