Degrees incorporating this pedagocial element :
Description
This interdisciplinary MSc course is designed for applicants with a biomedical, computational or mathematical background. It provides students with the necessary skills to produce effective research in bioinformatics and computational biology.
The objective is to provide a short introduction on bioinformatics modelling and advanced tools for the analysis of sequence data. The first part of the course focuses on application in molecular biology and evolution, including hierarchical clustering and the analysis of phylogenetic and population genetic data.
The second part of the course focuses on machine learning for biological data, and includes change point detection in sequences and unsupervised clustering of massive genetic data. The course is evaluated with two lab-works, one for each part of the course.
Recommended prerequisite
Basic statistics (Poisson distribution), algorithmic (complexity), programming (python required, and R or Matlab).
In brief
Period : Semester 9Credits : 3
Number of hours
- Lectures (CM) : 36h
Hing methods : In person
Location(s) : Grenoble
Language(s) : English
Contact(s)
Clovis Galiez