Kirsten ten Tusscher

This study investigates when combining mechanistic and machine learning models improves predictions of gene regulatory network dynamics using synthetic data.

The paper explains how the balance between PLETHORA protein complexes and unbound PLETHORA determines regenerative competence in Arabidopsis roots, revealing a ratiometric mechanism for transcription factor dosage.

This study uses oscillator dynamics and auxin signaling models to argue against a genetic root clock driving lateral root priming, highlighting limitations in single-cell oscillation and phase memory.

The paper discusses the importance of robustness in scientific research, using split-root assays in Arabidopsis thaliana to highlight challenges in replicability and provide recommendations for improving experimental protocols.

This study quantifies the transport properties of canonical PIN-FORMED proteins and shows the loop domain's role in auxin transport beyond activation.

The paper uses quantitative modeling to investigate fate specification in the C. elegans postembryonic M lineage and identifies potential missing spatiotemporal signals.

The paper uses computational modeling to show auxin concentration initiates prebranch site formation, while auxin signaling capacity maintains it, resolving a debate on their roles in lateral root development.

This study develops a computational model to show that auxin transport dynamics and root growth jointly drive lateral root priming through temporal and spatial auxin fluctuations.