Notice
5.6. The diversity of bioinformatics algorithms
- document 1 document 2 document 3
- niveau 1 niveau 2 niveau 3
Descriptif
In this course, we have seen a very little set of bioinformatic algorithms. There exist numerous various algorithms in bioinformatics which deal with a large span of classes of problems. For example, read assembly. We have seen how NGS sequencers produce large sets of reads, small sequences which overlap. And the problem of assembly isto use the overlap in order to ordering this read and reconstructing the whole genomic sequence. This is the overlapping and you see that you can use this overlap to get a longer sequence. Of course, here the example issimple: you have to imagine a set of millions of reads to beassembled into genomic sequences of millions or billions of bases. A second class of problems issequence mapping and comparison. We have seen sequence comparison. What about sequence mapping? You remember this situation in which biologists get what they call "cDNA". Experimentally, this is a sequence of DNA and they want to map this sequence of DNA on the sequence of the genome in order to say: well, this is an exon, this i an exon and so on.
Thème
Documentation
Dans la même collection
-
5.1. The tree of life
RECHENMANN François
Welcome to this fifth and last week of our course on genomes and algorithms that is the computer analysis of genetic information. During this week, we will firstsee what phylogenetic trees are and how
-
5.4. The UPGMA algorithm
RECHENMANN François
We know how to fill an array with the values of the distances between sequences, pairs of sequences which are available in the file. This array of distances will be the input of our algorithm for
-
5.2. The tree, an abstract object
RECHENMANN François
When we speak of trees, of species,of phylogenetic trees, of course, it's a metaphoric view of a real tree. Our trees are abstract objects. Here is a tree and the different components of this tree.
-
5.5. Differences are not always what they look like
RECHENMANN François
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
-
5.3. Building an array of distances
RECHENMANN François
So using the sequences of homologous gene between several species, our aim is to reconstruct phylogenetic tree of the corresponding species. For this, we have to comparesequences and compute distances
-
5.7. The application domains in microbiology
RECHENMANN François
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
Avec les mêmes intervenants et intervenantes
-
1.6. GC and AT contents of DNA sequence
RECHENMANN François
We have designed our first algorithmfor counting nucleotides. Remember, what we have writtenin pseudo code is first declaration of variables. We have several integer variables that are variables which
-
2.5. Implementing the genetic code
RECHENMANN François
Remember we were designing our translation algorithm and since we are a bit lazy, we decided to make the hypothesis that there was the adequate function forimplementing the genetic code. It's now time
-
3.2. A simple algorithm for gene prediction
RECHENMANN François
Based on the principle we statedin the last session, we will now write in pseudo code a firstalgorithm for locating genes on a bacterial genome. Remember first how this algorithm should work, we first
-
3.10. Gene prediction in eukaryotic genomes
RECHENMANN François
If it is possible to have verygood predictions for bacterial genes, it's certainly not the caseyet for eukaryotic genomes. Eukaryotic cells have manydifferences in comparison to prokaryotic cells. You
-
4.8. A recursive algorithm
RECHENMANN François
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
-
5.7. The application domains in microbiology
RECHENMANN François
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
-
1.1. The cell, atom of the living world
RECHENMANN François
Welcome 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
-
1.9. Predicting the origin of DNA replication?
RECHENMANN François
We have seen a nice algorithm to draw, let's say, a DNA sequence. We will see that first, we have to correct a little bit this algorithm. And then we will see how such as imple algorithm can provide
-
2.8. DNA sequencing
RECHENMANN François
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
-
3.5. Making the predictions more reliable
RECHENMANN François
We have got a bacterial gene predictor but the way this predictor works is rather crude and if we want to have more reliable results, we have to inject into this algorithmmore biological knowledge. We
-
4.6. A path is optimal if all its sub-paths are optimal
RECHENMANN François
A sequence alignment between two sequences is a path in a grid. So that, an optimal sequence alignmentis an optimal path in the same grid. We'll see now that a property of this optimal path provides
-
5.1. The tree of life
RECHENMANN François
Welcome to this fifth and last week of our course on genomes and algorithms that is the computer analysis of genetic information. During this week, we will firstsee what phylogenetic trees are and how
