Building on a strong foundation of philosophy, theory, methods and computation over the
past three decades, Bayesian approaches are now an integral part of the toolkit for most …

Computational models are not just appealing because they can simulate and predict the
development of biological phenomena across multiple spatial and temporal scales, but also …

Simulation-based inference techniques are indispensable for parameter estimation of
mechanistic and simulable models with intractable likelihoods. While traditional statistical …

We combine an off-lattice agent-based mathematical model and experimentation to explore
filamentous growth of a yeast colony. Under environmental stress, Saccharomyces …

Computational models of tumor growth are valuable for simulating the dynamics of cancer
progression and treatment responses. In particular, agent-based models (ABMs) tracking …

Computational models are invaluable in capturing the complexities of real-world biological
processes. Yet, the selection of appropriate algorithms for inference tasks, especially when …

Understanding how genetically encoded rules drive and guide complex neuronal growth
processes is essential to comprehending the brain's architecture, and agent-based models …

The accurate assessment of cardiac motion is crucial for diagnosing and monitoring
cardiovascular diseases. In this context, digital volume correlation (DVC) has emerged as a …

Simulation based inference (SBI) methods enable the estimation of posterior distributions
when the likelihood function is intractable, but where model simulation is feasible. Popular …

During embryonic development of the retina of the eye, astrocytes, a type of glial cell,
migrate over the retinal surface and form a dynamic mesh. This mesh then serves as …