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Why does the Needleman-Wunsch algorithm use dynamic programming?
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bioinformatics
This computerized image of anthrax shows the various structural relationships of seven units within the protein and demonstrates the interaction of a drug (shown in yellow) bound to the protein to block the so-called lethal factor unit. Bioinformatics plays an important role in enabling scientists to predict where a drug molecule will bind within a protein, given the individual structures of the molecules.
The Needleman-Wunsch algorithm utilizes dynamic programming because it provides a systematic method to guarantee the discovery of an optimal alignment between two sequences.1
By employing this approach, the algorithm breaks down the complex, large-scale problem of aligning full sequences into a series of smaller, more manageable subproblems involving short sequence segments. It then uses the solutions derived from these smaller segments to construct the final, optimal solution for the entire sequence. This process involves scoring sequence similarities within a matrix, which also allows the algorithm to effectively detect gaps in the alignment.1