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Fiche de cours

Computational biology driving experimental design

Faculté de gestion: Ecole doctorale (FBM-DOCT)

Responsable(s): Roman Arguello, Marc Robinson-Rechavi

Période de validité: 2018 ->

Horaires du cours (Apériodique)

Date Lieu Remarque Thématique Intervenant(s)
22.02.2021 de 09:00 à 17:00 Génopode   Roman Arguello, Marc Robinson-Rechavi
23.02.2021 de 09:00 à 17:00 Génopode   Roman Arguello, Marc Robinson-Rechavi
24.02.2021 de 09:00 à 17:00 Génopode   Roman Arguello, Marc Robinson-Rechavi
05.03.2021 de 09:00 à 17:00 Génopode   Roman Arguello, Marc Robinson-Rechavi

Cours

Annuel
Apériodique
Langue(s) d'enseignement: anglais
Public: Oui
Crédits: 1.50

Objectif

The goal of this course is to prepare computational biologists and bioinformaticians to take the lead in designing experiments and data collection, and to prepare experimental biologists to use computational biology thinking in designing their experiments. The students will learn to leverage their strengths and combine them with other fields, to plan combined experimental and computational research projects which are informative about hypotheses in biology.

Contenu

In a first 3-day block, after an introduction, the students will propose research projects, first alone and then in pairs. These projects will be presented informally and receive feedback.
On a fourth day, the students will work on improving their project and will present it to the class. They will also provide a short written description.
There will be continuous feedback opportunities during the course.

Evaluation

Travail personnel de préparation: oui
Présentation personnelle: oui
Test final: non
Évaluation de la participation par l'enseignant: oui

Exigences du cursus d'études

This course targets PhD students in computational biology and bioinformatics, or in experimental biology with a strong interest in computational biology. Students are expected to be at ease in both basic biology and basic statistics, programming and modeling. No direct experience with experimental biology is required.

Conditions d'octroi

Évaluation positive de la participation par le tuteur

UtilisationCode facultéStatutCrédits
Doctorat en médecine et ès sciences (MD-PhD) (2010 ->) ›› Cours de 3e cycle de l'Ecole doctoraleED-QBOptionnel1.50
Doctorat ès sciences de la vie (2003 ->) ›› Cours de 3e cycle de l'Ecole doctoraleED-QBOptionnel1.50
Doctorat ès sciences de la vie - Ecology and Evolution (2007 ->) ›› Cours de 3e cycle de l'Ecole doctoraleED-QBOptionnel1.50
Doctorat ès sciences de la vie - programme Cancer and Immunology (2008 ->) ›› Cours de 3e cycle de l'Ecole doctoraleED-QBOptionnel1.50
Doctorat ès sciences de la vie - programme Cardiovasculaire et métabolisme (2005 ->) ›› Cours de 3e cycle de l'Ecole doctoraleED-QBOptionnel1.50
Doctorat ès sciences de la vie - programme Integrated Experimental and Computational Biology (2010 ->) ›› Cours de 3e cycle de l'Ecole doctoraleED-QBOptionnel1.50
Doctorat ès sciences de la vie - programme Microbial Sciences (2010 ->) ›› Cours de 3e cycle de l'Ecole doctoraleED-QBOptionnel1.50
Doctorat ès sciences de la vie - programme Quantitative Biology (2018 ->) ›› Cours de 3e cycle de l'Ecole doctoraleED-QBOptionnel1.50
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