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Finding Approximate Multiple Alignment Bo Brinkman and Martin Tompa Abstract We develop an algorithm which finds approximately optimal alignments for the general case of k sequences. Our goal is to increase the effectiveness of known methods (such as dynamic programming) by applying them in a new way. 1. Introduction 2. The Basic Algorithm 1. Split the k sequences into two groups using some method 2. Align these two groups to each other using dynamic programming 3. Treat the output alignment as a list of sequences, and go to step 1 3. Scoring function 3.1 Relative Entropy Scoring of DNA DP ab g ab Bk g Bk t || B lg Bk t ab 3.2 SP-Measure Dayhoff Scoring for Proteins In our program we use the SP-measure along with a scoring matrix which assigns a score to the pairing of any two amino acids. 4. Grouping Techniques 5. Concluding Remarks 1. Tuning Gap and Space Penalties 2. Explore Effect of Local Optima 3. More Advanced Grouping Methods Created by : Kuen-Feng Huang Date : May. 31, 2000