Quantitative Biology
Statistical learning is essential for individuals to discover structure in the sensory environment, especially during communication via speech or music. Individual differences in statistical learning abilities have been proposed to account…
\textbf{Background:} In Costa Rica, dengue is reported and controlled at the canton level, and outbreaks in one canton are often followed by outbreaks in others. Climate models describe where conditions favor transmission but not how dengue…
Phylogenetic trees are rooted trees with branch lengths that record genetic divergence or elapsed time, and quantifying differences between them is central to a wide range of evolutionary and epidemiological analyses. Graph-polynomial…
With the enormous advances in cerebral imaging techniques, a large amount of data is available for studying the aging and demented brain. In this contribution, we apply the OASIS-3 dataset for identifying small areas of the human gray…
ssys is a Python package for exact algebraic recasting of supported ODE models into S-system or Generalized Mass Action form. It reads Antimony and SBML models, introduces auxiliary variables through symbolic lifting, and validates…
We propose a mathematical framework for organizational psychology based on a Maximum Entropy model of a group's personalities. The Maximum Entropy model is then decimated to a single ``collective personality''. If the original personality…
Embodied artificial intelligence is moving from deployable models to persistent agents that learn in the field, acquire skills and migrate across bodies. Governing such a system means governing an individual, not a model, and existing…
Artificial Intelligence has had a profound impact on the biological sciences, and in particular has accelerated research on protein form and function. Enzymes are no exception: a surge of predictive models have been recently developed to…
Understanding the differences between individual instances of the same complex system remains a central challenge, particularly in biological contexts. Parenclitic networks constitute a suitable means to detect deviations in correlations…
Comparing whether two dynamical systems implement the same computation despite differences in coordinates or measurements is a central problem in neuroscience and machine learning. Dynamical Similarity Analysis [DSA; Ostrow et al., 2023]…
We propose and analyse a mathematical model of evolutionary adaptation for non-degenerate (permanent) replicator systems, in which the fitness landscape matrix evolves on a slow timescale -- the evolutionary time -- while the species…
We mathematically model the dynamics of the number of migratory fish observed at a fixed location along a river in a random environment. Particularly, as a new approach, we construct a stochastic differential equation that incorporates the…
How can a species persist in an environment where it is always outcompeted? Using a minimal predator-prey model with environment-dependent parameters, we show that a predator driven to extinction in each of two static environments can…
This work presents a stochastic exploration framework for large, implicitly defined chemical reaction spaces that are too large to be generated and stored as explicit molecular networks. The exploration strategy mimics stochastic chemical…
Generative models present a promising alternative to expensive molecular dynamics for computationally querying protein dynamics, yet many existing approaches treat ensembles as unordered snapshots rather than temporally coherent…
Arthur Guyton's classic pressure-natriuresis model posits that dietary sodium challenges induce a transient expansion of blood volume that the kidneys rapidly rectify to restore a strict homeostatic baseline, reducing cardiac output to…
Multi-compartment Hodgkin-Huxley (HH) models provide a principled framework for predicting neural dynamics and responses to electrical stimulation. However, fitting HH biophysical parameters typically requires intracellular recordings,…
DNA methylation (DNAm) serves as one of the most robust molecular biomarkers of biological aging. While conventional epigenetic clocks accurately predict chronological age from high-dimensional CpG profiles, they treat aging as a static…
Precise sound localization relies on microsecond sensitivity to interaural time differences (ITDs), yet binaural perception exhibits sluggish tracking of dynamic acoustic cues. How these properties coexist remains unresolved. Here, ITD is…
Codon harmonization aims to adapt the coding sequences for heterologous expression while preserving the native-like patterns of frequent and rare codons that may influence local translation dynamics and co-translational protein folding.…