multiple_alignment

multiple_alignment - University of North Texas Biocomputing...

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    Biocomputing University of North Texas Multiple Alignment Source: www.bioalgorithms.info
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  University of North Texas Biocomputing Multiple Alignment versus Pairwise Alignment Up until now we have only tried to align two sequences.
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  University of North Texas Biocomputing Multiple Alignment versus Pairwise Alignment Up until now we have only tried to align two sequences. What about more than two? And what for? A faint similarity between two sequences becomes significant if present in many Multiple alignments can reveal subtle similarities that pairwise alignments do not reveal
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  University of North Texas Biocomputing Generalizing the Notion of Pairwise Alignment Alignment of 2 sequences is represented as a 2-row matrix In a similar way, we represent alignment of 3 sequences as a 3-row matrix   A T _ G C G _   A _ C G T _ A   A T C A C _ A Score: more conserved columns, better alignment
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  University of North Texas Biocomputing Alignments = Paths in Align 3 sequences: ATGC, AATC,ATGC A A T -- C A -- T G C -- A T G C
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  University of North Texas Biocomputing Alignment Paths 0 1 1 2 3 4 0 1 2 3 3 4 A A T -- C A -- T G C 0 0 1 2 3 4 -- A T G C Resulting path in (x,y,z) space: (0,0,0) (1,1,0) (1,2,1) (2,3,2) (3,3,3) (4,4,4) x coordinate y coordinate z coordinate
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  University of North Texas Biocomputing 2-D vs 3-D Alignment Grid V W 2-D edit graph 3-D edit graph
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  University of North Texas Biocomputing Architecture of 3-D Alignment Cell (i-1,j-1,k-1) (i,j-1,k-1) (i,j-1,k) (i-1,j-1,k) (i-1,j,k) (i,j,k) (i-1,j,k-1) (i,j,k-1)
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  University of North Texas Biocomputing Multiple Alignment: Dynamic Programming s i,j,k = max 2200 δ ( x, y, z ) is an entry in the 3-D scoring matrix s i-1,j-1,k-1 + (v i , w j , u k ) s i-1,j-1,k + (v i , w j , _ ) s i-1,j,k-1 + (v i , _, u k ) s i,j-1,k-1 + (_, w j , u k ) s i-1,j,k + (v i , _ , _) s i,j-1,k + (_, w j , _) s i,j,k-1 + (_, _, u k ) cube diagonal: no indels face diagonal: one indel edge diagonal: two indels
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  University of North Texas Biocomputing Multiple Alignment: Running Time For 3 sequences of length n , the run time is 7 n 3 ; O( n 3 ) For k sequences, build a k -dimensional Manhattan, with run time ( 2 k -1)( n k ); O( 2 k n k ) Conclusion: dynamic programming approach for alignment between two sequences is easily extended to k sequences but it is impractical due to exponential running time
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  University of North Texas Biocomputing Multiple Alignment Induces Pairwise Alignments
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multiple_alignment - University of North Texas Biocomputing...

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