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1.7. DNA walk
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We will now design a more graphical algorithm which is called "the DNA walk". We shall see what does it mean "DNA walk". Walk on to DNA. Something like that, yes. But first, just have a look again at the typical, also quite short sequence of DNA, a long text offour letters: A, C, G, T, T and so on. When the first sequence of DNA were obtained, the idea of using computers very quickly emerged but people didn't know exactly what to do with this sequence of characters. Again, there is a meaning behind the sequence because it is genetic information. It means it is the information which defines a living organism which defines how it survives, how it reproduces, how it works. So, it has a meaning. How can we discover this meaningin a text again without any markers, spaces and so on. There were some strange ideas but quite sympathetic ideas. A first idea was to say: well, can we turn these genetic sequences into music. Because, we have sequences of characters. Music is a sequence of notes, so maybe we could transform a genetic sequence into a sequenceof notes and make music. And perhaps hearing the music,we will get some ideas about what the meaning of the sequence is. Of course, if we have 4 letters,we only have 4 frequencies.
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1.4. What is an algorithm?
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1.8. Compressing the DNA walk
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1.2. At the heart of the cell: the DNA macromolecule
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1.5. Counting nucleotides
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1.9. Predicting the origin of DNA replication?
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1.3. DNA codes for genetic information
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1.6. GC and AT contents of DNA sequence
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1.1. The cell, atom of the living world
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1.10. Overlapping sliding window
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1.1. The cell, atom of the living world
RechenmannFrançoisWelcome to this introduction to bioinformatics. We will speak of genomes and algorithms. More specifically, we will see how genetic information can be analysed by algorithms. In these five weeks to
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1.10. Overlapping sliding window
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2.3. The genetic code
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3.6. Boyer-Moore algorithm
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4.5. A sequence alignment as a path
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5.5. Differences are not always what they look like
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1.4. What is an algorithm?
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2.4. A translation algorithm
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3.1. All genes end on a stop codon
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