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2.6. Algorithms + data structures = programs
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By writing the Lookup GeneticCode Function, we completed our translation algorithm. So we may ask the question about the algorithm, does it terminate? Andthe answer is yes, obviously. Is it pertinent, that is, doesit return the expected answer? The answer is yes, if you giveas an input a sequence of DNA, you will get as an output asequence of amino acids unless, of course, one of the tripletsis not one of the 64 expected triplets and then you will get, ofcourse, a nonsense protein sequence. Is it efficient? Well, for measuring the efficiency of an algorithm, you can ask the question, how manybasic operations you have to execute. In that case the critical operationis comparison of letters. In the best case if you are lucky,the algorithm for looking up a triplet needs three comparisons,if you're not lucky, in the worst case, it needs 64 comparisons. These are not high numbers, ofcourse, but you have to remember that you have to execute the Lookup Algorithm for every triplet of the sequence so a sequencemay be very very long so it may be a good idea to ask the question: can we do better? And the answer is yes. For doing better, what we can introduce is a data structure. Here is the data structure inthe left part of this slide.
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2.1. The sequence as a model of DNA
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2.4. A translation algorithm
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2.8. DNA sequencing
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2.5. Implementing the genetic code
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2.9. Whole genome sequencing
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2.3. The genetic code
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4.10. How efficient is this algorithm?
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