Biology subjects

Roesch, E.

Publications and source records attributed to Roesch, E..

4 recordsLinked to original sources

bioRxiv2021

Uncertainty in cell fate decision making: Lessons from potential landscapes of bifurcation systems

Cell fate decision making is known to be a complex process and is still far from being understood. The intrinsic complexity, but also features such as molecular noise represent challenges for modelling these systems. Waddingtons epigenetic landscape has become the overriding metaphor for developmental processes: it both serves as pictorial representation, and can be related to mathematical models. In this work we investigate how the landscape is affected by noise in the underlying system. Specifically, we focus on those systems where minor changes in the parameters cause major changes in the stability properties of the system, especially bifurcations. We analyse and quantify the changes in the landscapes shape as the effects of noise increase. We find ample evidence for intricate interplay between noise and dynamics which can lead to qualitative change in a systems dynamics and hence the corresponding landscape. In particular, we find that the effects can be most pronounced in the vicinity of the bifurcation point of the underlying deterministic dynamical systems, which would correspond to the cell fate decision event in cellular differentiation processes.

systems biology↗

bioRxiv2019

GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation

Approximate Bayesian computation (ABC) is an important framework within which to infer the structure and parameters of a systems biology model. It is especially suitable for biological systems with stochastic and nonlinear dynamics, for which the likelihood functions are intractable. However, the associated computational cost often limits ABC to models that are relatively quick to simulate in practice. We here present a Julia package, GpABC, that implements parameter inference and model selection for deterministic or stochastic models using i) standard rejection ABC or ABC-SMC, or ii) ABC with Gaussian process emulation. The latter significantly reduces the computational cost.\n\nURL: https://github.com/tanhevg/GpABC.jl

systems biology↗

bioRxiv2019

Parameter inference in dynamical systems with co-dimension 1 bifurcations

Dynamical systems with intricate behaviour are all-pervasive in biology. Many of the most interesting biological processes indicate the presence of bifurcations, i.e. phenomena where a small change in a system parameter causes qualitatively different behaviour. Bifurcation theory has become a rich field of research in its own right and evaluating the bifurcation behaviour of a given dynamical system can be challenging. An even greater challenge, however, is to learn the bifurcation structure of dynamical systems from data, where the precise model structure is not known. Here we study one aspects of this problem: the practical implications that the presence of bifurcations has on our ability to infer model parameters and initial conditions from empirical data; we focus on the canonical co-dimension 1 bifurcations and provide a comprehensive analysis of how dynamics, and our ability to infer kinetic parameters are linked. The picture thus emerging is surprisingly nuanced and suggests that identification of the qualitative dynamics -- the bifurcation diagram -- should precede any attempt at inferring kinetic parameters.

systems biology↗

bioRxiv2019

An EEG study of detection without localisation in change blindness

Previous studies of change blindness have suggested a distinction between detection and localisation of changes in a visual scene. Using a simple paradigm with an array of coloured squares, the present study aimed to further investigate differences in event-related potentials (ERPs) between trials in which participants could detect the presence of a colour change but not identify the location of the change (sense trials), versus those where participants could both detect and localise the change (localise trials). Individual differences in performance were controlled for by adjusting the difficulty of the task in real time. Behaviourally, reaction times for sense, blind, and false alarm trials were distinguishable when comparing across levels of participant certainty. In the EEG data, we found no significant differences in the visual awareness negativity ERP, contrary to previous findings. In the N2pc range, both awareness conditions (localise and sense) were significantly different to trials with no change detection (blind trials), suggesting that this ERP is not dependent on explicit awareness. Within the late parietal positivity range, all conditions were significantly different. These results suggest that changes can be sensed without knowledge of the location of the changing object, and that participant certainty scores can provide valuable information about the perception of changes in change blindness.

neuroscience↗