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Nombre de programmes trouvés : 536
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le (7m26s)

5.7. The application domains in microbiology

Bioinformatics relies on many domains of mathematics and computer science. Of course, algorithms themselves on character strings are important in bioinformatics, we have seen them. Algorithms and trees, for example,for reconstructing phylogenetic trees, algorithms on networks toreconstruct gene interaction networks, metabolic networks and maybe to simulate the dynamics of the time. We have seen also the implicationof probability and statistics. The implication of optimizationmethods, for example, for the computation of the optimalalignment of a pair of sequences. Constraint satisfaction is used forpredicting molecule structure. Automata and formal grammarswhich are some exotic parts of computer science are also usefulin bioinformatics, the same for signal processing. And soother domains may be listed here. We also ...
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Label UNT Clip pédagogique

le (7m26s)

Remediation - Vecteurs position, vitesses et accélérations décrits en coordonnées cartésiennes et polaires - VIDEO 19- Mouvement circulaire uniforme (suite)

... vecteur accélération non nulle.Cet élément de remédiation permet d'expliquer cette réponse.Etant donné que les positions, vitesses et accélérations sont décrits par des vecteurs,nous rappellerons quelques propriétés utiles sur la façon de se repérer dans...
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le (7m30s)

1.10. Overlapping sliding window

We have made some drawings along a genomic sequence. And we have seen that although the algorithm is quite simple, even if some points of the algorithmare bit trickier than the others, we were able to produce an interesting result that is a prediction of the origin of replication of bacterial genomes. We have seen also that it may work for a large part of bacterial genomes but for some of them it doesn't work and this is the real life of bio informaticians. We have to deal with that. But, our algorithm was very visual. Now, we want to have a more quantitative approach to make apparent the ...
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le (7m40s)

5.5. Differences are not always what they look like

The algorithm we have presented works on an array of distance between sequences. These distances are evaluated on the basis of differences between the sequences. The problem is that behind the differences we observed on the set of sequences, there may beother mutations which cannot be observed and we should modify the distances. We will have a look at some simple cases of these observed differences which may correspond to hidden differences and then we will see how the evaluation, computationof the number of differences may be affected. The simple case is this one, aunique substitution between, in the sequence One we have a Cand it turns out that in ...
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le (7m42s)

4.8. A recursive algorithm

We have seen how we can computethe optimal cost, the ending node of our grid if we know the optimal cost of the three adjacent nodes. This is this computation scheme we can see here using the notation of the pseudo code and not the mathematical notation we used in the previous sessions. So again we can compute the cost of this node if we know the cost of that node, that node and that node and we have to add respectively the insertion cost, the substitution cost orthe insertion cost. The substitution cost here depends on the letter at this position in the sequence and this letter ...
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Label UNT Vidéocours

le (8m22s)

2.8. DNA sequencing

During the last session, I explained several times how it was important to increase the efficiency of sequences processing algorithm because sequences arevery long and there are large volumes of sequences, so it's now the time to ask: but where these sequences come from? This is the process of sequencing. DNA sequencing is a physical operation through which a DNA molecule is read, that is every nucleotide along the strand of the molecule is read and then a text is producedas a succession of the nucleotides as letters. So from the DNA molecule tothe text through what is a sequencer. Sequencers are smaller and smaller and smaller and they ...
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