Less eec1ve to compare coding regions at nucleo1de

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Unformatted text preview: atch (T). j=2, i=4,5,7 is a match (T). Since vi = wj, si,j = si-1,j-1 +1 s2,2 s2,5 s4,2 s5,2 s7,2 = = = = = [s1,1 [s1,4 [s3,1 [s4,1 [s6,1 = = = = = 1] 1] 1] 1] 1] + + + + + 1 1 1 1 1 Backtracking Example Con1nuing with the dynamic programming algorithm gives this result. Scoring Matrices •  The alignment score represent odds of obtaining that score between sequences known to be related to that obtained by chance alignment between unrelated sequences •  When the correct scoring matrix is used, alignment sta1s1cs are meaningful •  Different scoring schemes for DNA and protein sequences Examples of Scoring Matrices •  Amino acid subs1tu1on matrices: –  PAM –  BLOSUM •  DNA subs1tu1on matrices: –  DNA is less conserved than protein sequences. –  Less effec1ve to compare coding regions at nucleo1de level. Scoring Indels: Naive Approach •  A fixed penalty σ is given to every indel: –   ­σ for 1 indel, –   ­2σ for 2 consecu1ve indels –   ­3σ for 3 consecu1ve indels, etc. Can be too severe penalty for a series of 100 consecu1ve indels Affine Gap Penal1es •  A series of k indels oZen come as a single event rather than a series of k single nucleo1de events: This is more likely. Normal scoring would This is less give the same score likely. for both alig...
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This note was uploaded on 02/10/2014 for the course CS 680 taught by Professor Staff during the Fall '08 term at Colorado State.

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