Notice
5.2. The tree, an abstract object
- document 1 document 2 document 3
- niveau 1 niveau 2 niveau 3
Descriptif
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. Here is what we call an edge or a branch. We have nodes, a particular nodeis the root and other nodes are the leaves here terminal nodesand we see that when we draw a tree as an abstract object, we put the root upside and the leaves downside so it's the reverse of a classical natural tree. We need an expression to describe a tree and we will use this kind of expression, how does it work? It uses parenthesis and you see that this means that part of the tree, this that part of thetree and then it's easy to see that, that part of the expression refers to this and the final expression refers to the whole tree. OK. A tree expression, we willuse this kind of expression when describing the execution of our phylogenetic tree or reconstruction algorithm. Of course it doesn't matter howthe tree is drawn, it could be like that with the same leaves and it is the same topology and so it is the same tree expression.
Thème
Documentation
Dans la même collection
-
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
-
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
-
5.5. 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
-
5.6. The diversity of bioinformatics algorithms
RECHENMANN François
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,
-
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
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
