Master Thesis Online
Data-driven Inference of a TF-regulated Metabolic Network for photosynthetic organism modelling: Chlamydomonas Reinhardtii.
Waterplas, Dries 
Promotor(s) :
Meyer, Patrick
Date of defense : 7-Sep-2018 • Permalink : http://hdl.handle.net/2268.2/5438
Mémoire2018_Waterplas_Dries.pdf
Mémoire2018_WD_ABSTR_N_ABBREV.pdfDetails
| Title : | Data-driven Inference of a TF-regulated Metabolic Network for photosynthetic organism modelling: Chlamydomonas Reinhardtii. |
| Translated title : | [fr] Inférence d'un réseau métaboliques sous régulation de TF pour la modélisation d'organismes photosynthétiques: Chlamydomoans Reinhardtii |
| Author : | Waterplas, Dries
|
| Date of defense : | 7-Sep-2018 |
| Advisor(s) : | Meyer, Patrick
|
| Committee's member(s) : | Baurain, Denis
Farnir, Frédéric
Cardol, Pierre
|
| Language : | English |
| Number of pages : | 74 |
| Keywords : | [fr] Chlamydomonas Reinhardtii Metabolic Network Constraint-Based Modelling Transcriptomic Regulation |
| Discipline(s) : | Life sciences > Biochemistry, biophysics & molecular biology |
| Research unit : | BioSys : Bioinformatics and Systems Biology Lab |
| Name of the research project : | Improving metabolic models of photosynthetic organisms using regulation from TRN-Inference |
| Target public : | Researchers Professionals of domain Student |
| Institution(s) : | Université de Liège, Liège, Belgique |
| Degree: | Master en biochimie et biologie moléculaire et cellulaire, à finalité spécialisée en bioinformatique et modélisation |
| Faculty: | Master thesis of the Faculté des Sciences |
Abstract
[fr] Metabolic pathways involved in photosynthesis and biosynthesis of lipids, hydrogen or growth are typically regulated by complex interdependent mechanisms involving multiple fronts of omics (genomics, transcriptomics, proteomics, …). Here, we apply Constraint-Based Modelling (CBM) techniques on a genome-scale metabolic network reconstruction of C. reinhardtii, and improve the model by integrating constraints from a Transcriptional Regulation Network, thus taking into account cell gene expression shifts under envrionmental changes.
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