Peter Kováč. Bioinformatics of Sequences with Repetitive Motifs. Master thesis, Comenius University in Bratislava, 2012. Supervised by Tomáš Vinař.
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We present a method for alignment of two sequences containing repetitive motifs. This is motivated by a biological studies of proteins with zinc finger domain, an important group of regulatory proteins. Due to their evolutionary history, se- quences of these proteins contain a variable number of different zinc fingers (short subsequences with specific symbols at each position). Our algorithm uti- lizes two types of hidden Markov models (HMM) for accomplishment of the task: pair HMMs and profile HMMs. The dynamic programming algorithm that com- putes the motif alignments is based on the well known Viterbi algorithm. We evaluated our model on real world sequences of zinc finger proteins and were able to outperform existing solution. Keywords: sequence alignment, hidden Markov model, dynamic programming.