Global Sequence Alignment: the Needleman-âWunsch Algorithm

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Implicit Column Scoring FuncLon • 1, match • 0, mismatch (mutaLon) • 0, gap (inserLon, deleLon) ASLVN-DK! A-LVNKDK! 10111011=6! • Sum the score over all columns of alignment. Deriving more complex scoring schemes will be a main topic of my next lecture.
Idea: How can we find an opLmal alignment? – Enumerate all possible alignments of s 1 and s 2 . – Calculate score using the column scoring funcLon. – Pick the alignment(s) with the highest score. Why is this a terrible idea?
Page 1 and 2: Global Sequence Alignment: the
Page 3 and 4: What is the intuiLon behind s
Page 5 and 6: Why align sequences? • Alignme
Page 7 and 8: Why align sequences? Alignments
Page 9 and 10: There are many possible alignme
Page 11: Which is the best alignment? s
Page 15 and 16: So what can we do?
Page 17 and 18: Some NotaLon • s 1 [1..i] = t
Page 19 and 20: The Key Insight • Think about
Page 21 and 22: Dynamic Programming Approach •
Page 23 and 24: Start with base condiLons D(i,j
Page 25 and 26: Now compute M(i,j) row by row.
Page 27 and 28: Now compute M(i,j) row by row.
Page 29 and 30: How do we construct an opLmal
Page 31 and 32: Is this algorithm feasible? •
Page 33 and 34: When would you want a local a

Global Sequence Alignment: the Needleman-âWunsch Algorithm

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Global Sequence Alignment: the Needleman-âWunsch Algorithm