Algorithms on Sequences

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Needleman & Wunsh’s algorithm (6) T A G A C T T A A C T 0 -2 -4 -6 -8 -10 -2 -4 -6 -8 -10 -12 2 0 -2 -4 -6 -8 0 4 2 -2 2 -4 -6 0 -2 2 1 -1 0 4 2 0 -2 -4 2 0 6 4 4 8 S I,J-1 - Gap S I,J = Max S I-1,J-1 + Sub (X I ,Y J ) S I-1,J - Gap match M = 2 mismatch N = -2 Gap = 2 result = ? Needleman & Wunsh’s algorithm (7) T A G A C T T A A C T 0 -2 -4 -6 -8 -10 -2 -4 -6 -8 -10 -12 2 0 0 -2 -4 -6 -8 4 2 -2 2 -4 -6 0 -2 2 0 -2 0 4 2 0 -2 -4 2 0 6 4 4 8 Determinati<strong>on</strong> of the optimal alignment T 2 T A 4 A - 2 G A 4 A C 6 C T 8 T
Smith & Waterman algorithm (1) • local alignments between 2 sequences ccggttcttcttacaacgtgcataaagccagcacaagaaagt cgtagtacggtcattagaccccgcagtgagccttacgt ac.gtgcataa.agccag || || ||| | | || | acggt.cattagaccccg Smith & Waterman algorithm (2) • The score S N,M is calculated from the recurrence equati<strong>on</strong> : 0 S I,J-1 - Gap S I,J = Max S I-1,J-1 + Sub (X I ,Y J ) S I-1,J - Gap Dynamic Programming
Page 1 and 2: Bioinformatics Algorithms</
Page 3 and 4: Alignment of two sequences • Matc
Page 5 and 6: DP applied to alignments • Given
Page 7: Needleman & Wunsh’s algorithm (4)
Page 11 and 12: E I,J = MAX Gotoh’s algorithm (2)
Page 13 and 14: Identity and default Blast Matrices
Page 15 and 16: Other substitution matrices • Phy
Page 17 and 18: Example 1 : easy case ALIGN calcula
Page 19 and 20: Validation of a global alignment (2
Page 21 and 22: PRSS compares a test sequence to a
Page 23 and 24: BLASTN 1.4.7 [16-Oct-94] [Build 17:
Page 25 and 26: Principle of the heuristics (1) 1 -
Page 27 and 28: Tradeoff sensitivity / rapidity W 1
Page 29 and 30: Recent Blasts • Blast2 (Gapped Bl

Algorithms on Sequences

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