# lec06 - CSE 427 Computational Biology Multiple Sequence...

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CSE 427 Computational Biology Multiple Sequence Alignment

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Motivations Common structure, function, or origin may be only weakly reﬂected in sequence; multiple comparisons may highlight weak signal Major uses represent protein families deduce evolutionary history
Multiple Sequence Alignment Defn: An alignment of S 1 , S 2 , …, S k , is a set of strings S’ 1 , S’ 2 , …, S’ k , (with spaces) s.t. (1) |S’ 1 | = | S’ 2 |= …= | S’ k |, and (2) removing all spaces leaves S 1 , S 2 , …, S k a c b c d b a c – – b c d b c a d b d – c a d b – d – a c a b c d a c a – b c d –

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Multiple Alignment Scoring Varying goals 3 examples: Consensus string; sum distances to it Align to (evolutionary) tree; sum edges SP score: S um of P airs abcde acde xccxd abcde ac-de xccxd ACCDE abcde ac-de xccxd Σ i D(S i ,C) Σ i<j D(S i ,S j )
Optimal SP Alignment via DP k strings of length n (n+1) x (n+1) x ⋅⋅⋅ x (n+1) k-dim array Max of 2 k -1 neighbors per cell; (n+1) k cells Time: at least (2n) k Want n, k 10’s to 100’s Unlikely to do dramatically better - it’s NP-complete E.g., n = 100 10 6 ops/sec k Time 2 40 ms 3 8 sec 4 .5 hr 5 100 hrs 6 2 years

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## This note was uploaded on 04/22/2008 for the course CSC 427 taught by Professor Ruzzo during the Winter '08 term at University of Washington.

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lec06 - CSE 427 Computational Biology Multiple Sequence...

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