3 credits
30.0 h
Q1
Teacher(s)
Draye Xavier coordinator; Lobet Guillaume;
Language
French
Prerequisites
Mathematics, informatics, biology, physiology and genetics (typ. masters BIRA et BBMC).
Main themes
- Introduction to systems biology
- Introduction to notions of dynamic and compartmentalized networks
- Mathematical formalisms and software tools for the exploration of omics data
- Initiation to modelling (practicals)
- Introduction to notions of dynamic and compartmentalized networks
- Mathematical formalisms and software tools for the exploration of omics data
- Initiation to modelling (practicals)
Aims
At the end of this learning unit, the student is able to : | |
| 1 | a. Contribution of this activity to the program learning outcomes M1.1, M1.2, M2.2, M2.3, M3.1, M3.6, M4.4, M6.1, M6.3, M6.4
b. Learning outcome specifics for this activity At the end of the course, the student is able to : · approach the functioning of an organism in a systems framework and at multiple scales ; · explain the specifics of systems biology · recognise and understand a systems biology methodology · explore the litterature with professional databases (e.g. Scopus), contact and discuss with researchers in the field · present a subject in a synthetic and pedagocis way to the student room |
The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Content
Table of content
1. General view of systems biology
Systems theory and biology
Topology, graphs and network attributes
Node identification and interactions mapping
Network inference
Data integration
From structure to dynamics
2. Software tools for data mining of omics
3. Languages and case studies
L-Systems (structure) and FSPM (structure-function)
Interactions organism - environment
Case studies at different scales (gene network, cell, tissue, organ, organism)
1. General view of systems biology
Systems theory and biology
Topology, graphs and network attributes
Node identification and interactions mapping
Network inference
Data integration
From structure to dynamics
2. Software tools for data mining of omics
3. Languages and case studies
L-Systems (structure) and FSPM (structure-function)
Interactions organism - environment
Case studies at different scales (gene network, cell, tissue, organ, organism)
Teaching methods
Presentation of one or more seminars
Directed practicals (in classroom). Article reading, use of models or modeling languages.
Directed practicals (in classroom). Article reading, use of models or modeling languages.
Evaluation methods
Presentation of one or more seminar
Evaluation of the participation to the class work
Evaluation of the participation to the class work
Other information
This course can be given in English.
Online resources
Moodle
Bibliography
Articles choisis de la littérature (liste revue chaque année).
Déposés sur Moodle.
Déposés sur Moodle.
Faculty or entity
AGRO
