Bioinformatics: Genomes and Algorithms
- Effort: 13 hours
- Pace: Self paced
- Enrollment
- From Feb. 15, 2017 to ...
- Course
- From May 15, 2017 to July 2, 2017
- Languages
- English
What you will learn
At the end of this course, you will be able to:
joint approach to genomics and algorithmics, or if you prefer, to algorithmics and genomics.
Description
Exceptionally, this archived course remains open to registrations although it is not facilitated by the course teachers: its contents are no longer updated (course contents were created in 2015). All collaborative spaces are closed: you cannot interact with the teaching team or with other learners. Furthermore, no attestation of achievement will be delivered.
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.
Format
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, using static Jupyter notebooks.
Prerequisites
A scientific culture will make easier the understanding of the notions studied.
Assessment and certification
No attestation of achievement will be delivered for this course. Only the french version of the Mooc allows you to have this attestation.
Course plan
- Week 1 : Genomic texts
- Week 2 : Genes and proteins
- Week 3 : Gene prediction
- Week 4 : Sequences comparison
- Week 5 : Phylogenetic trees
Other course runs
Ongoing
- From May 13, 2019 to May 14, 2021
Archived
- From May 15, 2017 to July 2, 2017
- From May 4, 2015 to June 8, 2015
Course team
Thierry Parmentelat
Organizations
License
License for the course content
Attribution-NonCommercial-NoDerivatives
You are free to:
- Share — copy and redistribute the material in any medium or format
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes.
- NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
License for the content created by course participants
Attribution-NonCommercial-NoDerivatives
You are free to:
- Share — copy and redistribute the material in any medium or format
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes.
- NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
