Space_efficient_Align - Space Efficient Sequence Alignment...

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Space Efficient Sequence Alignment A Divide-and Conquer Algorithm : The limiting resource for computing the dynamic programming computation table is not the running time but the storage or space required to to store the table. We will present a linear space algorithm [Hirschberg,1975] at the expense of doubling the computation time using a divide-and conquer algorithm.
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Computing Alignment Path Requires Quadratic Memory Alignment Path Space complexity for computing alignment path for sequences of length n and m is O( nm ) We need to keep all backtracking references in memory to reconstruct the path (backtracking) n m
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Memory Alignment Score Space complexity of computing just the score itself is O( n ) We only need the previous column to calculate the current column, and we can then throw away that previous column once we’re done using it. Alternately, we can do the same row-by-row. But to find longest path in the edit graph, we need to store all the backtracking pointers which takes O ( nm ) space. 2
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This note was uploaded on 06/12/2011 for the course CAP 5510 taught by Professor Staff during the Spring '08 term at University of Central Florida.

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Space_efficient_Align - Space Efficient Sequence Alignment...

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