Teacher(s)

Gatto Laurent;

Language

French

Prerequisites

The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.

Main themes

This introduction to bioinformatics and data science applied to biomedical sciences will introduce students methodologies and technologies used in bioinformatics. They will learn how to manage bioinformatics projects and how to manipulate and visualise data of average size.

Aims

At the end of this learning unit, the student is able to :
1	After this course, the students will understand what bioinformatics is and when to use it. They will be able to   Analyse a simple bionformatics problem, and implement a bioinformatics solution to solve it.   Decompose a problem in simpler sub-problems and solve these as analysis scripts.   Read and understand existing scripts.   Use informatics tools to help and support their programming tasks.   Understand technical documentation for the R programming language and Bioconductor vignettes.   Write their own R scripts and small analysis reports in Rmd.   This course contributes to the leaning goals 2a, 2c, 3c, 5a, 5b, 5c, 5d of the bachelor's programme in biomedical sciences.

Content

This introductory course to bioinformatics will focus on the following themes:

• What is bioinformatics and it application domains.
• Technologies and methodologies used in bioinformatics.
• Introduction to omics data and technologies.

The data science applications to biomedical sciences will focus on:

• Data analysis project management and reproducible research.
• Spreadsheets for data organisation.
• The RStudio programming environment.
• Data analysis and programming in R.
• Introduction to data structures in R.
• Data handling and visualisation.
• High throughput data with R and Bioconductor.

Teaching methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

The course will be composed of practical sessions, during which the students will implement solutions to data analysis problems relevant to biomedical sciences using the R programming language and the RStudio development environment.
Course attendance to all sessions (volume 1 and 2) is mandatory. In case of repeated unjustified absence, further attendance to the final exams might be excluded.

Evaluation methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

Continuous evaluation: the students will be given regular test throughout the course. Those that have and average mark equal or greater than 12 will be dispensed of the final exam.
The final exam will be practical and computer-based; the students will prepare a reproducible report in Rmd using RStudio answering exam questions addressing small scale data analysis task similar to those presented during the course. The test scores will be ignored when taking the final exam.

Online resources

Teaching materials

• cours en ligne et informations complémentaires sur moodle. Obligatoires.

Faculty or entity

SBIM