Jan Rombouts

Jan Rombouts
European Molecular Biology Laboratory | EMBL · Cell Biology and Biophysics Unit (Heidelberg)

PhD
EIPOD Postdoctoral Fellow at EMBL Heidelberg

About

25
Publications
1,933
Reads
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70
Citations
Citations since 2016
23 Research Items
69 Citations
20162017201820192020202120220510152025
20162017201820192020202120220510152025
20162017201820192020202120220510152025
20162017201820192020202120220510152025
Additional affiliations
November 2016 - present
KU Leuven
Position
  • PhD Student
Description
  • I work on mathematical modeling of the cell cycle, with a focus on models that include a time delay.
September 2014 - June 2015
The University of Warwick
Position
  • Master's Student
April 2014 - June 2014
Ecole Normale Supérieure de Paris
Position
  • Research Internship

Publications

Publications (25)
Article
Full-text available
Railway systems form an important means of transport across the world. However, congestions or disruptions may significantly decrease these systems’ efficiencies, making predicting and understanding the resulting train delays a priority for railway organisations. Delays are studied in a wide variety of models, which usually simulate trains as discr...
Article
Full-text available
Modeling biochemical reactions by means of differential equations often results in systems with a large number of variables and parameters. As this might complicate the interpretation and generalization of the obtained results, it is often desirable to reduce the complexity of the model. One way to accomplish this is by replacing the detailed react...
Article
In oscillatory media, waves can be generated by pacemaker regions which oscillate faster than their surroundings. In many chemical and biological systems, such waves can synchronize the whole medium and as such they are a means of transmitting information at a fixed speed over large distances. In this paper, we apply analytical tools to investigate...
Preprint
Full-text available
Railway systems form an important means of transport across the world. However, congestions or disruptions may significantly decrease these systems' efficiencies, making predicting and understanding the resulting train delays a priority for railway organisations. Delays are studied in a wide variety of models, which usually simulate trains as discr...
Preprint
Full-text available
In an oscillatory medium, a region which oscillates faster than its surroundings can act as a source of outgoing waves. Such pacemaker-generated waves can synchronize the whole medium and are present in many chemical and biological systems, where they are a means of transmitting information at a fixed speed over large distances. In this paper, we a...
Preprint
Full-text available
Modeling biochemical reactions by means of differential equations often results in systems with a large number of variables and parameters. As this might complicate the interpretation and generalization of the obtained results, it is often desirable to reduce the complexity of the model. One way to accomplish this is by replacing the detailed react...
Article
Full-text available
Bistability is a common mechanism to ensure robust and irreversible cell cycle transitions. Whenever biological parameters or external conditions change such that a threshold is crossed, the system abruptly switches between different cell cycle states. Experimental studies have uncovered mechanisms that can make the shape of the bistable response c...
Article
Full-text available
In an oscillatory medium, a region which oscillates faster than its surroundings can act as a source of outgoing waves. Such pacemaker-generated waves can synchronize the whole medium and are present in many physical and biological systems, where they are a means of transmitting information. Through numerical simulations, we quantify how the proper...
Article
Full-text available
Spatially extended oscillatory systems can be entrained by pacemakers, regions that oscillate with a higher frequency than the rest of the medium. Entrainment happens through waves originating at a pacemaker. Typically, biological and chemical media can contain multiple pacemaker regions, which compete with each other. In this paper, we perform a d...
Article
Chromosome segregation during mitosis is antagonistically regulated by the Aurora-B kinase and RepoMan-associated phosphatases PP1/PP2A. Aurora B is overexpressed in many cancers but, surprisingly, this only rarely causes lethal aneuploidy. Here we show that RepoMan abundance is regulated by the same mechanisms that control Aurora B, including FOXM...
Article
Full-text available
We review a series of key travelling front problems in reaction–diffusion systems with a time-delayed feedback, appearing in ecology, nonlinear optics and neurobiology. For each problem, we determine asymptotic approximations for the wave shape and its speed. Particular attention is devoted to their validity and all analytical solutions are compare...
Article
Full-text available
Time delays are known to play a crucial role in generating biological oscillations. The early embryonic cell cycle in the frog Xenopus laevis is one such example. Although various mathematical models of this oscillating system exist, it is not clear how to best model the required time delay. Here, we study a simple cell cycle model that produces os...
Data
A time delay destabilizes the steady state. The system settles into a constant, stable, steady state if the time delay is low (left). For increasing time delays, the system first exhibits damped oscillations (middle) and finally the steady state becomes unstable and sustained oscillations occur (right). The time delay at which the state becomes uns...
Data
Oscillation period in the distributed delay model. The period of the oscillation as function of N for different values of m and τ. Higher N corresponds to more peaked distributions. The period depends very little on N from a certain point onwards. The main influence on the period comes from τ. This figure supplements Fig 4 in the main text. (PDF)
Data
Length of S phase and M phase as function of c and τ. In the main text (Fig 3D) we show the duration of S phase and M phase in the m → ∞ model. We concluded that they are equal for c ≈ 1/2. This picture shows that this holds too for the model with finite m. (PDF)
Data
Amplitude as function of τ1 and τ2 for low c in state-dependent delay model. Amplitude as function of τ1 and τ2, for low c. Corresponds to Fig 5D in the main text, which shows the period. The black line indicates where M and S phase have equal duration. Other parameters: ks = 1.2 nM/min, bdeg = 0.125 min−1, m = 20, β = 5 min−1, p = 5. (PDF)
Data
Oscillation amplitude in the distributed delay model. The amplitude of the oscillation as function of N for different values of m and τ. Higher N corresponds to more peaked distributions. In contrast to the period, the amplitude is influenced by all the parameters in this plot. This figure supplements Fig 4 in the main text. (PDF)
Data
Amplitude as function of m and τ. The amplitude of the oscillation (activity of Cdk1) as a function of m and τ. Compare with Fig 2E in the main text. Whereas the period jumps at the boundary, the amplitude increases gradually from 0 at the boundary to larger values farther away. The amplitude is influenced by m too, where the period depends almost...
Data
Amplitude as function of ks and bdeg. The amplitude of the oscillation (activity of Cdk1) as a function of ks and bdeg. Compare with Fig 2F in the main text. Whereas the period jumps at the boundary, the amplitude increases gradually from 0 at the boundary to larger values farther away. (PDF)
Data
Amplitude as function of τ1 and τ2 for high c in state-dependent delay model. Same as S7 Fig, but with a high value of c. Corresponds to Fig 5E in the main text. Other parameters: ks = 1 nM/min, bdeg = 0.0625 min−1, m = 20, β = 5min−1, p = 5. (PDF)
Data
Amplitude as function of bdeg and τ1. Amplitude as function of bdeg and τ1. Corresponds to Fig 5F in the main text, which shows the period. The sum of τ1 and τ2 is fixed at 15 minutes and ks = 1.25 nM/min, m = 20, β = 5 min−1, p = 5. The line shows which values give an equal length of M and S phase. (PDF)
Data
Supplementary information. This file contains the mathematical analysis of the models and XPPAUT code for running model simulations. (PDF)
Article
Full-text available
We formulate and analyze a simple dynamical systems model for climate–vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet,...
Article
Full-text available
We formulate and analyze a simple dynamical systems model for climate–vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet,...

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