Exceptionally, this archived course remains open to registrations although it is not facilitated by the course teachers: its contents are no longer updated and may therefore no longer be up to date (course contents were created in 2015).
If you register, you can freely consult the read-only resources but all collaborative spaces are closed (forums, wiki and other collaborative exercises): you cannot interact with the teaching team or with other learners.
Furthermore, no attestation of achievement will be delivered for this course.
In this course, you will discover how computer science supports the interpretation of the text of genomes. Running the adequate programs, a computer may produce predictions on the location of the thousands of genes in a living organism and the functions of the proteins these genes code for.
You are not a biologist? Attending this course, you will be introduced to several entities and processes involved in the interpretation of the genomic texts: cell, chromosome, DNA, genome, genes, transcription, translation, proteins and many more.
You are not a computer scientist? This course is also an introduction to algorithms on character strings: pattern searching, sequence similarity, Markov chain models, or phylogenetic tree reconstruction are some basic algorithms which are implied in genome sequence analysis and will be explained.
You are neither a biologist nor a computer scientist? This course is a great opportunity to a joint approach to genomics and algorithmics, or if you prefer, to algorithmics and genomics.
NEW in this session: thanks to a specific tool (iPython notebooks), you will be able to execute the algorithms presented in the course and evaluate their use on real data sets. If you wish to go further, the iPython notebooks allow you to modify the programs written in Python and you can even code new ones and test them.
The course is structured in 5 weeks.
Each week, new material will be available: around 10 course sequences with a 6 minutes video, quizzes associated to each sequence, course documents and practical exercices at the end of each week.
The algorithms shown in the course will be also presented in Python and executable via the iPython notebooks integrated to the course. Thanks to this tool, you will be able to modify the algorithms and even to write new ones.
A scientific culture will make easier the understanding of the notions studied.
- Week 1 : Genomic texts
- Week 2 : Genes and proteins
- Week 3 : Gene prediction
- Week 4 : Sequences comparison
- Week 5 : Phylogenetic trees