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le (6m25s)

1.8. Compressing the DNA walk

We have written the algorithm for the circle DNA walk. Just a precision here: the kind of drawing we get has nothing to do with the physical drawing of the DNA molecule. It is a symbolic representation. It is a way of representing the information content of the sequence as a drawing. Remember that the problem of the algorithm we designed is that it supposes the capacity of drawing several millions or billions of segments on the screen. This is not feasible. No screen will be large enough for that. So, how can we deal with this hardware constraint? Compression is the answer. Let's see that in more details. Remember, for each ...
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le (6m23s)

3.4. Predicting all the genes in a sequence

We have written an algorithm whichis able to locate potential genes on a sequence but only on one phase because we are looking triplets after triplets. Now remember that the genes maybe located on different phases and on the two strands. It means that to retrieve all the genes on a genome we have to look on six different sequences, three phases on each strand. Let's looknow how we can deal with this kind of search. First we have to modify a little bit our algorithm so that instead of starting at position One, I want to introduce a variable, a parameter which could be One or Two ...
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le (6m10s)

2.4. A translation algorithm

We have seen that the genetic codeis a correspondence between the DNA or RNA sequences and aminoacid sequences that is proteins. Our aim here is to design atranslation algorithm, we make thehypothesis that the genetic codehas been implemented as an array as presented in the lastslide of the previous session. We have seen transcriptions and translationsfrom DNA to RNA and proteins. An important thing to notice hereis that most of the time computer scientists and bioinformaticiansjust forget about RNA. When they speak about translating,they say translating from DNA to proteins directly becausethe differences between the DNA and RNA is only T and U sowhat they do is this ...
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le (6m10s)

3.8. Probabilistic methods

Up to now, to predict our gene,we only rely on the process of searching certain strings or patterns. In order to further improve our gene predictor, the idea is to use, to rely onprobabilistic methods. What does it mean? I will firsttake an example, which is not related to genomic but I think it'sgood to understand the idea. Imagine you have a very long text which is known to be written in some human understandable language but you don't know which one but you know that some passages of this text only are written in a human understandable language,maybe English, maybe French and so on, whatever. You don't know. How ...
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