Algorithms on Sequences
Algorithms on Sequences
Algorithms on Sequences
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Principle of the heuristics (3)<br />
3 – Each hit is « extended » to produce an<br />
alignment<br />
hit<br />
Sequence of the bank<br />
AATCGGATTGCATAA<br />
ATGGACTGGC<br />
Query sequence<br />
alignment<br />
ATCGGATTG<br />
|| ||| ||<br />
AT.GGACTG<br />
Speed Gain of the heuristics<br />
• Example : 2 sequences of DNA of size 1000<br />
• Dynamic Programming :<br />
– 1000 x 1000 = 10 6 matrix-cells<br />
• Heuristics with W = 8<br />
– statistically :<br />
nb of hits = 10 6 x (1 / 4 8 ) = 15 (1 for W=10)<br />
– 1000 search in the dicti<strong>on</strong>nary (10 x 10 3 operati<strong>on</strong>s)<br />
– 15 extensi<strong>on</strong>s (15 x 10 3 operati<strong>on</strong>s)<br />
• Gain : 10 6 / 2.5 x 10 4 = 40 (87 for W=10)