Portrait of Victoria Mochulska is unavailable

Victoria Mochulska

PhD - McGill University
Supervisor
Paul François
Research Topics
Computational Biology
Dynamical Systems
Optimization

Publications

Generative epigenetic landscapes map the topology and topography of cell fates.
Victoria Mochulska
Paul François
Epigenetic landscapes were proposed by Waddington as the central concept to describe cell fate dynamics in a locally low-dimensional space. … (see more)In modern landscape models, attractors represent cell types, and stochastic jumps and bifurcations drive cellular decisions, allowing for quantitative and predictive descriptions. However, given a biological problem of interest, we still lack tools to infer and build possible Waddington landscapes systematically. In this study, we propose a generative model for deriving epigenetic landscapes compatible with data. To build the landscapes, we combine gradient and rotational vector fields composed of locally weighted elements that encode ‘valleys’ of the Waddington landscape, resulting in interpretable models. We optimize landscapes through computational evolution and illustrate our approach with two developmental examples: metazoan segmentation and neuromesoderm differentiation. In both cases, we obtain ensembles of solutions that reveal both known and novel landscapes in terms of topology and bifurcations. Conversely, topographic features appear strongly constrained by dynamical data, which suggests that our approach can generically derive interpretable and predictive epigenetic landscapes.
2025-12-15
PubMed (unknown)
doi.org
Dynamical model and geometric insights in the discontinuity theory of immunity
Christian Mauffette Denis
Victoria Mochulska
Maya Dagher
Vincent Verbavatz
François X.P. Bourassa
Grégoire Altan-Bonnet
Paul François
The immune system’s most basic task is to decide what is “self” and “non-self”, but a precise definition of self versus non-self r… (see more)emains challenging. According to the discontinuity theory of immunity, effector responses depend on how quickly an antigenic stimulus changes: rapid change triggers an immune response, whereas gradual change fosters tolerance. We present a model of adaptive immune dynamics including T cells, Tregs and cytokines that reproduces the hallmarks of the discontinuity theory. The model allows for sharp discrimination between acute and chronic infections based on the growth rate of the immune challenge, and vaccination-like acute dynamics upon presentation of a bolus of immune challenge. We further show that the model behavior only depends on a handful of testable assumptions that we map to geometric constraints in phase space. This suggests that the model properties are generic and robust across alternative mechanistic details. We also examine the impact of multiple concurrent immune challenges in this model, and demonstrate the occurrence of dynamical antagonism, wherein, in some parameter regimes, slow-growing challenges hinder acute responses to fast-growing ones, with further counter-intuitive behaviors for sequential co-infections. Together, these results place the discontinuity theory on firm mathematical footing and encourage further investigation of interferences of multi-agent immune challenges, from chronic viral co-infections to cancer immunoediting.
2025-07-17
bioRxiv (preprint)
doi.org