Research Overview
My research sits at the intersection of quantitative proteomics, bioinformatics, and experimental cell biology. I develop computational approaches to analyse large-scale mass spectrometry datasets and connect them to mechanistic models of the cell cycle. The central question: how do cells time mitosis with such extraordinary precision?
Postdoctoral Research
Temporal regulation of APC/C during mitosis
Working in the Kamenz Lab at the University of Groningen, I study how the Anaphase-Promoting Complex/Cyclosome (APC/C) is regulated over time during mitosis using Xenopus laevis egg extracts as a model system. Progressive phosphorylation acts as a molecular timing mechanism that controls substrate degradation order — giving cells a way to sequence mitotic events precisely.
Methods
- Quantitative proteomics
- Native mass spectrometry
- Crosslinking MS
- Xenopus laevis egg extracts
Key findings
- Progressive phosphorylation drives mitotic timing
- APC/C substrate ordering is temporally encoded
Tools
- MaxQuant, Peaks, DIA-NN
- Custom Python / C++ scripts
PhD Research
Quantification of proteome variations at the intact protein level
During my PhD at the Institut Jacques Monod (Camadro Lab, Université Paris Cité), I developed the bSLIM (bottom-up Simple Light Isotope Metabolic) labeling strategy — a novel quantitative proteomics workflow designed to improve the precision and depth of metabolic labeling experiments. The approach combines isotope labeling, advanced signal processing, and custom algorithms to measure proteome changes at scale.
Methods
- Isotope metabolic labeling
- Signal processing
- Computational modeling
- Top-down proteomics
Outputs
- 3 first-author publications
- Open-source algorithms (bSLIM)
- PhD thesis, 2022
Tools
- Proteome Discoverer
- MaxQuant
- R, Python