Tristetraprolin (TTP) is a messenger RNA (mRNA)-binding protein that targets pro-inflammatory mRNAs and recruits protein complexes that promote their degradation, making it a key regulator of inflammation resolution. TTP phosphorylation and activity are regulated by the mitogen-activated protein kinase (MAPK) p38 pathway, a cascade of phosphorylation events that also promotes the expression of...
Epidemics place strong pressure on healthcare systems, particularly on hospital and intensive care unit (ICU) capacity. In this work, we present an extended compartmental SAIR model to study epidemic dynamics and their interaction with healthcare resources. The model explicitly distinguishes between hospitalized and ICU patients, providing a detailed representation of hospital dynamics. It is...
The tumor microenvironment (TME) presents significant physical barriers, such as elevated interstitial fluid pressure (IFP) arising from disorganized and leaky vasculature together with a dense extracellular matrix (ECM). These barriers limit the effectiveness of systemic therapies by restricting drug penetration into the tumor core \cite{N20}. We develop a coupled mathematical model to...
We present a mathematical framework for quantifying basecalling error at multiple scales in single-molecule (nanopore) sequencing, from individual bases to whole-sequence classification.
We define hierarchical Phred-like quality scores — per-base, per-read, and per-sequence — and prove via Jensen's inequality that averaging in the Phred domain systematically overestimates accuracy relative to...
A fast and pathogen-specific supply of effector T cells is essential in the mammalian immune response to acute and chronic infections, as well as cancer. While the basic principles of T cell activation and differentiation are well established, the mechanisms that control the balance between proliferation and differentiation remain incompletely understood.
Motivated by the observation that...
Introduction: Quantifying tumor plasticity is essential for understanding resistance in glioblastoma (GBM). A mathematical pipeline is presented for the joint analysis of time-resolved single-cell (sc) transcriptomics and lineage barcoding to characterize cancer cell states and quantify their dynamics (proliferation, death, state transitions) in control or temozolimide-treated conditions. This...
This work presents a mathematical study of the progression of Alzheimer’s disease through a dynamical model based on ordinary differential equations. A detailed analysis is carried out on a biomarker cascade model which describes the sequential interaction between beta‑amyloid accumulation, tau hyperphosphorylation, neurodegeneration, and cognitive decline, in the line of the models introduced...
Understanding biological oscillators often requires reconstructing internal states from measurement time series. This becomes difficult when dynamics contain slow–fast manifolds that produce strongly nonlinear trajectories. Under such conditions, common state estimation methods face fundamental limitations. In particular, the Kalman–Bucy filter assumes system dynamics can be locally...
Understanding how the structure of biochemical reaction networks determines their long-term dynamical behavior remains one of the core problems in systems biology. Analysis of these models becomes increasingly challenging as network size and complexity grow. In this work, we present an enhanced framework for parameterizing the positive steady states of biochemical systems using the structural...
This poster presents a hands-on laboratory activity that introduces students to modeling water transfer processes across physical systems. Using simple experimental setups, students collect data on flow and transport, develop mathematical models to describe observed behavior, and test model predictions against measurements. The lesson connects concepts from biology, environmental science, and...
Early SARS-CoV-2 infection is governed by nonlinear and often antagonistic interactions among immune cells, cytokines, and intracellular signaling pathways. We developed a mechanistic agent-based model (ABM) of early lung infection integrating pneumocytes, macrophages, natural killer (NK) cells, type-I interferon (IFN) signaling, and the mTORC1 inhibitor sirolimus. To enable large-scale...
Immunotherapy has varied results and how to predict whether a patient will respond is an open question. It is crucial to closely monitor a patient’s response once immunotherapy begins, and to potentially change to an alternate treatment if needed. Using a mathematical model, Creemers et al. argued that a patient’s tumor growth rate and immune cell killing rate are the primary parameters...
Cancer spheroids capture the hallmark intratumoral heterogeneity of solid tumours, including phenotypic diversity and spatially distinct gene expression patterns, making them invaluable tools for studying therapeutic resistance. Differential receptor expression across tumour subpopulations remains a major challenge in cancer therapy, yet most computational models treat receptor proteins as a...
Human sleep and daytime sleepiness are fundamentally governed by the intricate interplay of two physiological processes: homeostatic sleep pressure and the circadian rhythm. Homeostatic sleep pressure represents the progressive accumulation of sleep propensity that builds continuously during periods of wakefulness and systematically dissipates during sleep. On the other side, circadian rhythm...
Cellular plasticity – the ability of cells to adapt to environmental changes by producing diverse phenotypes – plays a vital role in the reprogramming of cells across a broad spectrum of diseases, including cancer, diabetes, and neurodegeneration. It is also a key component of embryonic development and tissue remodelling. Targeting this plasticity is a promising therapeutic approach, as...
Health economic analyses are a key stage in implementing new technologies and policies in health care, supporting healthcare providers in making effective use of limited resources. While health economists and mathematical biologists both take quantitative approaches to problems in human health, health economic models typically do not take advantage of the full range of methods accessible to...
Pulsed field ablation (PFA) is an ablation technology for treatment of cardiac arrhythmias, which relies on electroporation. Although PFA has a nonthermal mechanism, some heating is expected due to the high power of the pulses. The presence of metallic cardiac implants may alter the electric field around the ablation catheter which may lead to increased heating. The aim was to investigate the...
This study develops and analyzes an SIRS epidemic model with convex incidence and saturated treatment under both autonomous and nonautonomous frameworks. For the autonomous system, we characterize the disease-free and endemic equilibria and perform a detailed bifurcation analysis, revealing backward and saddle-node bifurcations, as well as Hopf bifurcations that generate endemic bubbles....
Biofilms are complex, intricate colonies of bacteria that often attach to medical implants, causing complications and failure of medical procedures, including the need of implant removal, sepsis, and eventually loss of life. According to the National Biofilms Innovation Centre, biofilm contamination also represents an economical burden, leading to over £45 billion in financial losses yearly in...
Systems of intracellular biochemical reactions are highly complex, usually involving parts that cannot be directly measured. Representing these systems as networks, with nodes for biochemical species and edges, their reactions help to quantitatively characterize their function and the effects of dysregulation. Causal discovery methods can uncover interactions within these networks from...
Glioblastoma cells can form connected networks using tumor microtubes. Recently, it was discovered that through these connections glioblastoma cells can form a cell network which allows propagation of calcium waves. Additionally, there is a rare cell type called “periodic cell” which can sustain consistent intracellular calcium transients and is likely to have KCa3.1 pumps. In this work, we...
Current commercial EEG anesthesia monitoring systems put older patients at risk of overdose \cite{ni2019,obert2021influence}. Such monitors rely on frequency-domain EEG analysis, which assumes quasi-periodic stationary signals \cite{cohen2014}, but omitting phase data causes information loss. As EEG waveforms are often asymmetric \cite{cole2017}, an overlooked feature in the context of...
Adult Neurogenesis is the generation of neurons from neural stem cells after the juvenile development is completed. It is essential for the upkeep of cognitive functions and for reaction to injuries. To protect the cells from depletion and mutations, the cells cycle between dividing and non-dividing (quiescent) states. It has been seen experimentally that the quiescent cells are heterogeneous...
Cell invasion is a process in which cells degrade surrounding tissue and start populating the newly created space. It occurs in healthy and ill cells, during wound-healing but also during cancer. There are many mathematical models of different modalities and complexity levels that aim to describe and quantify this phenomenon. In this work, we compare the outputs of two partial differential...
Cells encode environmental information through the nuclear localisation dynamics of transcription factors (TFs) - stochastic time-series governed by physical parameters: mean expression (μ), coefficient of variation (CV), and autocorrelation time (T_ac). Labelling these is costly, motivating a foundational self-supervised model generalisable across TF localisations and biological contexts...
Fluctuations in red blood cell (RBC) membranes and chromatin domains encode key information about cellular mechanical properties and metabolic activity, which are often linked to physiological states and pathological alterations \cite{di_pierro_anomalous_2018}. Quantitative analysis of these fluctuations provides access to the underlying dynamics that characterize living systems as stochastic...
Abstract
This work presents an automated pipeline designed for the inference of the subcellular and population-level mechanome in red blood cells (RBCs). The system utilizes high-resolution spatial (65 nm/px) and medium-resolution temporal (30 Hz) video microscopy to capture the dynamics of cell membrane thermal fluctuations (flickering).
From a mathematical and data-driven...
Following the COVID-19 pandemic, seasonal infectious disease trend shifts have highlighted the need for advanced early warning systems. Conventional methods, such as change point detection and hockey-stick regression, are widely used but are designed for retrospective analysis. Building on these approaches, we aim to develop a generalized real-time early detection model based on bootstrap...
A novel mathematical model is developed that links the tuberculosis (TB) care cascade with the dynamics of healthcare worker adherence. The model extends standard TB compartmental frameworks by incorporating a health-worker supervision parameter and an evolutionary game for adherence to treatment protocols. We derive an analytic expression for the basic reproduction number $R_0(z)$ as a...
HIV remains a major global health challenge because antiretroviral therapy (ART) suppresses active virus but cannot eliminate the latent reservoir of infected CD4+ T cells, which can persist for years and reignite infection if treatment stops. New strategies are therefore needed to address viral latency. This theory project explores the use of DNA strand displacement (DSD) circuits to...
Tumour progression is shaped by a dynamic interaction between tumour cells and the immune system. One specific immunosuppressive mechanism to study tumour evasion causes cytotoxic T-cells, a major driving force of the immune system, to differentiate to an ‘exhaustive’ state where they have reduced immune effectiveness due to increased tumour interactions. While this is incorporated in existing...
Discovering differential equations governing dynamical systems is a fundamental challenge in mathematical biology, where mechanistic models are used to study complex processes such as gene regulation, cell fate decisions, and tumor dynamics. This becomes particularly difficult when experimental data is sparse. Generative Flow Networks (GFlowNets) are a probabilistic framework for generating...
Malaria remains a major global health concern. In the Republic of Korea, Plasmodium vivax is the dominant parasite and is characterized by both short- and long-incubation periods. Climate change has altered the mosquito habitats and expanded outbreak areas. However, the current malaria warning system in Korea is activated only when Plasmodium parasites are detected in captured mosquitoes. This...
Reaction-diffusion-ODE systems have emerged as powerful models for pattern formation in developmental biology, capturing the interplay between diffusive and non-diffusive nonlinear processes. These systems exhibit a rich variety of spatial structures, including classical Turing patterns and far-from-equilibrium patterns. Previous studies focused on diffusion-driven instability (DDI) generated...
Cells have several possible fates (diseases, differentiation, death). A way to describe those is via ‘cell trajectories’, in which the transcriptome of a cell evolves from a state A to a state B in a defined manner. Understanding transcriptome evolution is critical for identifying or improving treatments for various diseases. Here, we chose to study a particular cellular fate: differentiation....
Neuroblastoma is a significant health concern in children, as it is one of the most common types of cancer among this age group and is associated with poor survival rates. Currently, there are no effective therapies that significantly improve outcomes for these patients. This study explores the efficacy of Celyvir – an advanced therapy comprising mesenchymal stem cells carrying the oncolytic...
We present the main results from our recent work, extending methods from Mathematical Epidemiology (ME) to other systems that can be framed as Chemical Reaction Networks (CRNT).
Our main result concerns the stability of equilibria for positive system of differential equations. Positive systems appearing in CRNT have their dynamics determined by a family of forward-invariant faces of some...
Estimating time-varying cellular growth rates from time-lapse microscopy remains computationally challenging \cite{1}. Image segmentation errors propagate into size measurements, and because traditional methods rely on finite-difference approximations, they amplify this noise. This obscures biological fluctuations and forces reliance on moving averages that artificially flatten true...
Plasmids are extrachromosomal DNA molecules that replicate independently of the chromosome and are widely found in bacteria and other organisms. In nature, plasmids are ubiquitous and can carry various genes that play essential roles in the life of bacteria. In synthetic biology, plasmids are used as the standard tool to equip cells with designed gene circuits. Despite their importance, the...
Mathematical models of human thermoregulation are widely used to study temperature regulation in challenging environments, yet their complexity often limits the systematic analysis of long-term behaviour. Many established models include non-smooth, threshold-based mechanisms and do not explicitly represent the gradual loss of thermoregulatory capacity during prolonged cold exposure. In this...
We investigate the genotoxic effects that bacterial infections and antibiotics exert on human cells. Bacteria may induce mutations either by invading cells or by generating extracellular stress, and drugs can also have mutagenic effects. Moreover, complex interactions between the bacteria and the drug take place in the background. We modify the usual in-host pathogen models for chronic...
This work investigates the three species of one-predator-two-prey ecological models in Lotka-Volterra type functional response with or without diffusive terms.
Without the diffusive effects and under two essential assumptions, we generically classify all global dynamics completely. The global asymptotically stabilities of three equilibria are shown analytically in each case. Alternatively,...
The sense of olfaction (smell) in honeybees occurs through sensory receptors along their antennae. We study one type of sensor called a placode, which densely covers each antenna in a regular formation. Sitting close the antennae’s surface, each placode is covered by hundreds of innervated pores that capture olfactory particles. We seek to understand how the morphology and configuration of...
Population pharmacokinetic (PPK) modeling, as presented in \cite{ette2004population1} and \cite{mould2012basic}, offers a systematic approach for quantifying inter-individual variability and estimating population parameters in PK-PD models. Within this framework, co-variate effects on the pharmacokinetic parameters of the Schnider PK-PD model \cite{schnider1998influence}, commonly implemented...
Influenza is one of the respiratory diseases, and symptoms can be alleviated by treating with antiviral agents such as baloxavir, oseltamivir, laninamivir, and zanamivir. It is known to have high household transmission risk and the risk differs by age and treatment timing \cite{hirotsu_effect_2019}. Baloxavir is particularly effective at reducing secondary attack rate (SAR), and serial...
Approximate Bayesian Computation (ABC) is a common tool to tackle statistical inference problems for systems where the likelihood function is intractable, a feature common in biological settings due to the inherent complexity of the models under investigation. ABC replaces the likelihood with a comparison of experimental and simulated data, finding parameters which minimise any discrepancy. To...
Background & aims of study
With the increasing risk of malaria transmission driven by climate change and continued imported cases, understanding malaria dynamics from surveillance data has become important for disease control and public health preparedness. This study aims to infer incubation-related temporal structures and predict malaria incidence from time series using long short-term...
Metastasis is a major determinant of survival and treatment efficacy in cancer, yet the mechanisms by which the competition and interaction of heterogeneous tumor cell clones leads to metastasis remains poorly understood. Prior experiments comparing fluorescently barcoded models of human HER2+ breast cancer show that wild-type, d16, and p95 isoforms differ in their invasion and motility...
Circadian rhythms regulate a wide range of physiological processes, including core body temperature, hormone secretion, and cardiovascular activity. Among these, heart rate exhibits pronounced diurnal variation arising from endogenous circadian regulation. Despite this close relationship, the dynamical interaction between circadian rhythms and heart rate variation remains poorly...
Blinatumomab is a bi-specific T-cell engager that links CD3+ T-cells to CD19+ B-cells, leading to T-cell-mediated B-cell lysis. While it has improved outcomes in relapsed/refractory B-cell precursor ALL (r/r B-ALL), treatment response remains highly variable and the underlying immunological mechanisms are not fully understood.
T-cell exhaustion and impaired immune fitness may contribute to...
Colorectal cancer (CRC) remains a major cause of cancer morbidity and mortality, increasing mostly in adults younger than 50. Precision therapy and drug repurposing approaches may improve outcomes for patients who are ineligible for or do not respond to standard targeted therapy. We describe a computational framework that constructs individualized mechanistic “digital twin” models from patient...
BACKGROUND: Adaptive therapy delays drug resistance by modulating treatment instead of continuously applying the maximum tolerated dose \cite{1}. While Deep Reinforcement Learning (DRL) can optimize adaptive therapy in non-spatial, well-mixed deterministic tumor models \cite{2}, extending it to spatial models is challenging because tumor dynamics become stochastic and clinically observable...
The Susceptible–Infectious–Recovered (SIR) model has long been a foundational framework for modeling infectious diseases and has played an important role in informing public health policies during the COVID-19 pandemic. However, traditional SIR-based approaches primarily rely on epidemiological case data and often fail to account for behavioral and societal factors that influence disease...
We present a hybrid multiscale model that establishes a mechanistic link between tumour microenvironment dynamics and FDG-PET radiomic signatures. The key innovation is the integration of multiscale tumour modelling with synthetic PET-like image generation, enabling PET radiomic signatures to be interpreted in terms of underlying biological processes. The model integrates intracellular...
Gene calling is a critical step in genome annotation, where errors propagate into downstream biological interpretation. We present a hybrid approach that integrates machine learning into BBTools CallGenes by adding a neural advisory score to candidate open reading frames (ORFs) before dynamic-programming selection. Rather than replacing the existing gene-calling framework, the model...
Obesity is a major global public health issue characterized by an excessive accumulation of lipids that impairs health. White adipose tissue is responsible for this storage through its main cells, adipocytes. The expansion of this tissue relies on two mechanisms: an increase in adipocyte size (hypertrophy) and an increase in adipocyte number (hyperplasia). Although the combined effects of...
It has been hypothesised that a mechanism for antibiotic tolerance in bacterial biofilms -populations of bacteria embedded in an extracellular matrix - is the failure of the antibiotic to penetrate throughout the biofilm. In P. aeruginosa colonies for example, filamentous viral phages produced by bacterial cells have been shown to provide strong protection against antibiotics. Fluorescence...
Biological tissues are often subjected to forces, and modeling their response is crucial in cases like tumor growth or skin contraction to improve therapies. Linear elasticity is the simplest constitutive law, allowing superposition and fundamental solutions to analyze multiple force points, as illustrated by the immersed interface method \cite{roy2020immersed}. We discuss this principle in...
Cerebral autoregulation can be assessed by several methods in the ICU. Two of the most used methods are the Autoregulation Index (ARI) and mean velocity index (Mxa), but their agreement varies across patient populations. This study aims to evaluate their relationship in critically ill patients.
Transcranial Doppler recordings from 15 patients (46 paired ARI–Mxa measurements; median age 72...
Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer due to its propensity for early metastasis. MICAL (microtubule-associated monooxygenase) proteins, which are highly expressed within PDAC, directly induce actin depolymerization and indirectly cause cytoskeleton reorganization through transcription factors. Despite this knowledge, the holistic impact of MICAL2 on cytoskeleton states of...
Hormesis, a biphasic phenomenon of low-dose stimulation and high-dose inhibition, poses a modelling challenge due to nonlinear, history-dependent dynamics. Static curves cannot capture temporal evolution, hysteresis, or recovery. Existing approaches are empirical, high-dimensional, or lack explicit dose-memory, limiting their ability to capture hysteresis and recovery. Here we propose a...
The zebrafish serves as a powerful model of lifelong neurogenesis in vertebrates. Their Neural Stem Cells (NSCs) persist in specialized niches to generate neurons and glial cells, exhibiting high constitutive neurogenic activity and remarkable regenerative capacity \cite{Labusch2020, Grandel2006}.
Key gaps remain in understanding the molecular and cellular regulators of NSCs quiescence,...
Most adults are infected with the Epstein-Barr virus (EBV), which infects B cells and establishes lifelong latency. EBV achieves this by hijacking B cell-intrinsic transcriptional programs, which ultimately promotes B cell survival, including that of atypical memory B cells (ABCs), a population associated with autoimmune disease. Here, we aim to construct an ODE model of B cell fate...
The majority of ordinary differential equation models that exist in the literature focus on steady state equilibria or long-term outcomes, with very few emphasizing the transient nature of these systems of equations. In this work, we present a reduced system of ODEs to investigate the kinetics and transient nature of T cell activation in response to acute viral infection. Through an analysis...
We present a mathematical framework to describe tumor growth under PROTAC treatment, integrating PK, PD, and tumor growth inhibition. PROTACs are a new class of drugs that promote selective degradation of oncogenic proteins \cite{1}. Although preclinical studies show tumor shrinkage, relapse often occurs, suggesting resistance mechanisms \cite{2}. The model links PROTAC-induced protein...
Macroparasites, such as helminths, mosquitoes, and ticks, can impact host fitness and population dynamics, both directly and through the diseases they transmit. Climate change is expected to lead to macroparasite range shifts as habitats become more suitable towards the poles and less suitable towards the equator. These shifting distributions can have negative consequences on...
Ion channels play an essential role in brain communication networks. Mutations in the SCN1A gene encoding the alpha subunit of the voltage-gated sodium channel NAV1.1, expressed in the central nervous system, are responsible for severe epilepsy and migraines often resistant to treatments.
We used molecular dynamic simulations to investigate consequences of four clinically relevant SCN1A...
Organoids - 3D multicellular structures cultivated in vitro from self-aggregating stem cells - revolutionize preclinical research as an alternative to animal experimentation. But the design of in silico organoids is lagging behind, preventing modelling predictive control to optimize their characterization and production. The few numerical models developed mostly focus on tumoroids and do...
Follicular phase in the ovarian development involves two key mechanisms: follicle maturation (via cellular growth and mass increase) and competition among follicles. Capturing both remains challenging. Compartmental ODE models (e.g., \cite{Hendrix}) describe maturation through discrete stages and reproduce macroscopic dynamics, but neglect follicular competition and cellular maturation....
Endocrine regulatory systems play a pivotal role in preserving physiological homeostasis through intricate hormonal feedback mechanisms. Mathematical models formulated as systems of ordinary differential equations (ODEs) provide a quantitative framework for investigating the dynamics of such regulatory processes.
In this study, we examine established ODE models describing endocrine feedback...
Mental disorders are a major contributor to the global burden of disease and often manifest as overlapping symptom profiles rather than isolated diagnoses. In clinical and digital health settings, this requires simultaneous assessment of multiple psychiatric domains, including depression, anxiety, trauma-related symptoms, substance use, and suicidality. However, current screening frameworks...
The genus Sulfolobus includes some of the most extensively studied thermophilic Archaea and is notable for its metabolic versatility and relevance to industrial biotechnology. Genome-scale metabolic models (GEMs) enable predictive analyses of metabolism, but their reconstruction is complex, time consuming and sensitive to environmental assumptions, particularly during gap filling.
Here,...
One crucial part of modeling infectious disease dynamics is accurate parameter estimation. This study proposes a framework using physics-informed neural networks with metaheuristic hyperparameter tuning to estimate parameters in infectious disease models. For practical applicability, the method uses only infected case data while enforcing the governing differential equations during training....
Hematopoietic stem cells maintain the blood system. In previous work, we discovered that transitions between hematopoietic stem and multipotent progenitor cells can be controlled by mutual inhibition of MECOM and CDK6. High MECOM corresponds to a quiescent stem cell state and high CDK6 to a multipotent progenitor state. The IGF pathway, under the influence of metabolism and diet, promotes CDK6...
Metabolic reprogramming is a central hallmark of cancer, enabling tumor cells to sustain rapid proliferation and adapt to fluctuating nutrient availability and microenvironmental stress. In particular, the coupled dynamics of glucose consumption and lactate production provide insight into tumor metabolic phenotypes such as the Warburg effect and metabolic switching between glycolytic and...
Reaction-diffusion equations are central in ecological modeling for describing how biological populations, such as pathogens, propagate through space and time. While standard numerical methods such as finite difference and finite element schemes are well established for solving these equations, they can be difficult to integrate with data-driven inverse problems, particularly when estimating...
Propofol is a widely used intravenous anesthetic whose safe administration requires precise dosing to achieve adequate hypnosis while avoiding under- or overdosing. Pharmacokinetic–pharmacodynamic (PK-PD) models are commonly applied in target-controlled infusion systems to guide dosing based on patient characteristics and predicted effect-site concentrations.
This work compares model-based...
Protein aggregation plays a key role in the formation of many subcellular structures, ranging from lipid raft formation to protein cluster formation in postsynaptic domains. In many cases the underlying mechanism of protein aggregation involves diffusing particles being assimilated into protein clusters in the presence of a recycling process that exchanges particles with the cytosol. The...
Recent computational methods predict the binding affinity between pairs of proteins and ligands, often applied to evaluate how well a candidate drug might attach to a target protein. In complex-based protein-ligand affinity prediction, binding strength is inferred from the known 3-dimensional structures of protein-ligand complexes. State-of-the-art methods employ neural networks, but certain...
Previous studies have identified several drivers of influenza-like illness (ILI) incidence dynamics in temperate regions, yet it remains unclear whether these associations are reproducible across countries or shaped by local context. This study quantifies the relative contributions of climate and behavioral factors to ILI incidence dynamics across multiple European countries, using weekly...
Natural killer (NK) cells eliminate stressed and transformed cells by integrating signals from activating and inhibitory receptors. Although “serial killing” has been widely discussed, two quantitative gaps remain. First, it is unclear whether apparent serial killers reflect stable, intrinsic cytotoxic capacity differences, stochastic encounter dynamics, or both, making the definition...
Disease transmission unfolds on contact networks that are inherently dynamic, with interactions appearing and disappearing over time. Recent advances in GPS- and survey-based data collection have enabled reconstruction of time-dependent contact networks for entire communities. However, these observations are incomplete and noisy, making the resulting networks uncertain representations of the...
Introduction & Methods:
Alzheimer's disease (AD) progression involves the accumulation and spread of tau pathology, measurable via tau PET imaging. Conventional analyses using regional standardized uptake value ratios (SUVRs) obscure fine-grained spatial heterogeneity and early tau propagation. We developed an Implicit Neural Representation (INR) model to reconstruct voxel-level tau...
One of the most appealing characteristics of neural networks is their ability for data generalization and the extraction of data features that may initially appear obscure. In the context of dynamical systems reconstruction, this aptitude could facilitate advancements in the development of models based on experimental data. We investigate the extent to which neural networks can reproduce the...
Many non-pharmaceutical interventions (NPIs) were implemented to target contact patterns that drove wild-type SARS-CoV-2 transmission in Canada; however, it is challenging to determine and understand their individual and joint effectiveness in different age groups. We developed an age-structured Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model and stratified the population...
Intermittent fasting has been proposed as a potential strategy to modulate tumor progression through systemic metabolic regulation\cite{1}. In this work, we develop a mathematical framework that integrates a model of glucose homeostasis with a tumor growth law, enabling the study of how fasting schedules may influence tumor dynamics.
We first introduce a dynamical model of glucose metabolism...
Human neurodevelopmental disorders often originate from disruptions during early cortical development. This motivates the use of brain organoids which provide an experimental platform that recapitulates key aspects of human neurogenesis. However, brain organoid exhibit substantial variability in developmental dynamics due to intrinsic cellular heterogeneity. Although mathematical models have...
Mathematical models of biology commonly use differential equation formulations. Certain application areas, such as signal transduction modeling or scientific machine learning, involve models that contain many parameters. Efficient training of these models requires sensitivity analysis that scales well as the number of parameters grows. Hence, adjoint sensitivity analysis (ASA) is typically...
Sleepiness is commonly described by the two-process model, in which sleep pressure—a homeostatic drive that accumulates during wakefulness—and the circadian rhythm—an endogenous ~24-hour physiological cycle—interact to regulate alertness. Although this framework explains the primary fluctuations in alertness, substantial inter-individual variability remains unexplained. In this presentation,...
Biological neural networks (BNNs) are machine learning models that enhance the biological interpretability of artificial neural networks by modeling neural dynamics and providing insights underlying neural system behavior. In our previous work, Hodgkin-Huxley neuron models were implemented in BNNs to classify electroencephalogram (EEG) signals \cite{cruz2026bnn}. While biologically...
Background
Excess mortality captures the comprehensive burden of COVID-19, yet cross-national disparities remain poorly understood. We examined the impact of economic development and national preparedness on mortality outcomes across 59 countries from 2020 to 2024.
Methods
Countries were stratified by IMF economic classifications. We evaluated the association between the 2021 Global...
Cancer-associated fibroblasts (CAFs) play a key role in tumor progression by orchestrating complex signaling interactions within the tumor microenvironment. However, the regulatory architecture of CAF-mediated signaling networks remains poorly understood at the systems level. Microtubule-associated serine/threonine kinase-like (MASTL), a mitotic kinase involved in cell cycle regulation, has...
As immune cells circulate in the body, different factors may influence their movement, such as other immune cells, target cells, and the topology of the space \cite{Jerison2020}. This work investigates how confinement geometry influences T-cell motion and compares results with mathematical models in the literature. The analysis is based on experiments provided by the Swinburne team, focusing...
We present a computational framework for the mechanical characterization of leukemic cell nuclei integrating videomicroscopy, image-processing algorithms, and stochastic mechanics. The methodology has been developed within the Leukodomics project, aimed at constructing a digital twin for pediatric acute lymphoblastic leukemia.
Nuclear dynamics are quantified through automated tracking of...
Modern coexistence theory (MCT) has been the mainstay of coexistence research in recent years. While competition creates evolutionary changes in traits that affect coexistence, it can also induce rapid plastic changes in individuals. However, a generalised framework that integrates both plasticity and evolution into MCT is lacking. Here, we incorporated competition-induced plasticity into a...
Type-2 Diabetes Mellitus (T2DM) is characterised by dysregulated glucose levels involving complex interactions between insulin and glucagon. While delay differential equation (DDE) models of glucose-insulin dynamics reproduce ultradian oscillations \cite{bridgewater2020}, glucagon is often omitted despite its physiological role, and its dynamics are not well understood. In T2DM, $\alpha$-cell...
We extend the delayed logistic cell-population model of Baker and Röst. The generalized equation incorporates distributed delays expressed via both discrete and integral terms, and explicitly features the death rates of dividing and motile cells as parameters.
We first establish well-posedness, along with the nonnegativity and boundedness of biologically relevant solutions. We then derive...
Collaborative modeling and simulation become increasingly important to study complex disease processes across molecular to organism scales. To support collaborations and construction of digital twins in a modular way, we present Morpheus (https://morpheus.gitlab.io) - an extensible open-source software framework with user-friendly GUI to develop multiscale models in a modular manner and in a...
Norovirus is a primary agent of acute gastroenteritis in all age groups, with young children under five being particularly vulnerable. Due to the virus’s pronounced seasonal behavior, forecasting its detection rate based on climatic factors is essential. To characterize the periodic relationship between climate variables and norovirus detection rates, wavelet coherence analysis was applied....
Survival is commonly used as a primary endpoint in preclinical cancer studies to assess treatment effects across different dose levels. Using a preclinical immuno‑oncology study as a case study, we examine the limits of survival‑based dose‑response inference. Cox and AFT models indicate a statistically significant dose‑response effect. However, key dose‑response parameters show substantial...
According to the WHO, the implementation of potent double-dose vaccination programs helped significantly reduce COVID-19 case numbers and disease-acquired deaths during the pandemic. Thus, understanding the most efficacious control parameters of a double-dose vaccination strategy can be helpful in the control of emerging and re-emerging infections. To this end, we extended the traditional SEIR...
We present an image-driven computational model to enable patient-specific forecasting of triple-negative breast cancer (TNBC) response to neoadjuvant chemotherapy (NAC). Our approach integrates longitudinal magnetic resonance imaging (MRI) data with a biologically-based mechanistic model of tumor growth and therapy response.
Building upon our previously published model that couples drug...
Advances in experimental techniques allow brain activity to be measured at scale, for example using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Alongside experimental advances, computational platforms for simulating brain dynamics have also shown meaningful progress. Together, they have created new opportunities to understand spatiotemporal patterns of brain...
This research investigates the dynamic interplay between energy metabolism and protein homeostasis (proteostasis) under conditions of energetic stress. We present a two state kinetic model that tracks how proteins transition between unfolded and native conformations through synthesis, folding, unfolding, and degradation. This framework captures both transient and steady state behavior of the...
Rocuronium is a lipophobic neuromuscular blocking agent used to induce muscle relaxation during surgery. Although its pharmacokinetic (PK) and pharmacodynamic (PD) properites have been extensively studied, differences between normal-weight and obese patients remain insufficiently characterized. In particular, it is unclear whether Rocuronium dynamics and effects differ between these groups and...
Advances in cellular and tissue biology have enabled robust tracking of large populations of interacting cells while simultaneously collecting detailed, multiplex molecular measurements. In such data-rich settings, mathematical models provide a powerful framework for integrating observations, capturing cellular interactions, and explaining emergent collective behaviours.
A range of...
This poster concerns the coefficient inverse problem for Maxwell's equations, related to finding the space-dependent dielectric permittivity and effective conductivity functions using backscattered time-dependent electrical field in three dimensions. The aim is to reconstruct the dielectric properties of Malignant Melanoma tissue, both shape and values.
The forward problem is solved using a...
Genomics, metabolomics, and proteomics offer complementary insights into cardiovascular disease (CVD) risk. In this published work, we introduce the CardiOmicScore, a multitask deep learning framework, to learn disease-specific proteomic (ProScore) and metabolomic (MetScore) risk scores for the six most common CVDs by profiling 2920 proteins and 168 metabolites. Experiments demonstrate that...
Glioblastoma is a highly aggressive primary brain tumour characterised by rapid growth and diffuse infiltration into surrounding tissue, making complete surgical removal and effective treatment extremely challenging. An important feature of glioblastoma is the behaviour of tumour cells at the invasive margin, which drives the disease progression, highlighting the need for mathematical models...
Biological processes, e.g., growth, repair, and remodeling generate residual stresses that significantly alter the biomechanical response of biomedical materials. The present work develops the constitutive relations for residually stressed Arruda–Boyce materials through a numerical inverse analysis. The model is validated using Treloar’s uniaxial tension data, mapped to initially stressed...
Background and objectives
The transition to sentinel surveillance for SARS-CoV-2 has made it difficult to accurately determine the true scale of infections, underscoring the need for complementary indicators such as wastewater-based epidemiology (WBE). This study aims to estimate unobserved prevalence by developing a predictive framework that infers actual community-level infection scales...
The nuclear receptor Pregnane X Receptor (PXR) is a key regulator of metabolic enzymes and transporters, characterized by complex dynamics essential for maintaining metabolic homeostasis. While PXR-mediated regulation is well-documented, the kinetic mechanisms governing its temporal oscillations remain poorly quantified [1,2]. This work introduces a mathematical model to investigate the...
Chimeric antigen receptor T-cell (CAR T) therapy has demonstrated remarkable efficacy in hematological malignancies. However, resistance remains a major clinical challenge, as it can compromise treatment response and promote relapse. Among the mechanisms that may underlie resistance, loss or downregulation of the target antigen is particularly relevant, since it enables tumor cells to escape...
We consider the asymptotic problems of the Keller-Segel system with the nonlinear diffusion of porous medium type and logistic sensitivity. We classify three possible distinguished limits and reveal the relations between the Keller-Segel system and the limit systems. We prove that our model converges to three various limits as the parameters are chosen adequately: a porous medium equation when...
Cellular models based on single-cell RNAseq data have emerged as a common tool for a system-level exploration of cell mechanisms, especially relevant for tasks such as gene regulatory network (GRN) inference or cell trajectory prediction. Some early mechanistic models allow dataset simulation from GRNs, thus using underlying biological knowledge and offering greater interpretability. However,...
Epidemic models commonly assume Markovian disease progression, in which transitions between infection states occur at constant, memoryless rates. However, real infectious diseases are inherently history-dependent: the probability of becoming infectious depends on time since exposure, and latent and infectious periods rarely follow exponential distributions. This mismatch can bias epidemic...
Sleep spindles are hallmark thalamo-cortical oscillations of non-REM sleep implicated in memory processing and emotion regulation. We develop and analyze a Wilson–Cowan mean-field model of a corticothalamo-reticular circuit comprising cortical pyramidal and inhibitory populations, thalamic relay cells, and reticular thalamic populations, to capture spindle-like dynamics at the population...
Transporter-mediated drug delivery is a crucial factor in pharmacokinetic and pharmacodynamic (PK/PD) studies. Transporter kinetics are typically evaluated using the Michaelis–Menten (MM) model, which estimates the maximum reaction rate($V_{\max}$) and the Michaelis constant($K_M$). However, the MM model assumes a well-mixed environment, whereas transporters operate in localized spatial...
Chemical reaction networks (CRNs) are a commonly used model type in biology and chemistry (with applications in e.g. systems biology, pharmacology, and epidemiology). Here, we demonstrate Catalyst.jl, a flexible and feature-filled Julia library for the creation, simulation, and analysis of CRN models. Models can be created both using the Catalyst DSL (which enables the implementation of CRNs...
In cardiac electrophysiology, ionic currents at the subcellular scale drive electrical activity at the tissue scale, making accurate cellular modeling essential for understanding cardiac function. Experimental inaccessibility of subcellular compartments in intact tissue positions mathematical models as essential tools for studying excitation propagation and motivates the development of...
Radiopharmaceutical therapy with $^{177}$Lu–PSMA has emerged as an effective treatment for metastatic prostate cancer, yet current clinical protocols rely on empirically fixed and non-personalized schedules. A mechanistic mathematical model based on ordinary differential equations is introduced to integrate tumor growth dynamics, radiation damage and organs pharmacokinetics....
Angiogenesis is a hallmark of tumor growth. Strikingly, tumor vascular networks present a non-hierarchical, dense, high-permeability vascular structure. To better design personalised treatment strategies, it is important to characterise and understand the function of these altered vascular networks in different scenarios - namely, how does oxygen perfusion depend on vessel density.
In this...
An active pool of spermatogonial stem cells (SSCs) maintain male fertility. The effects of aging on the SSC pool remains poorly understood. Here, we used in vivo CRISPR barcoding to label zebrafish SSCs to study how SSC clones contribute to sperm production. We sampled sperm from barcoded zebrafish every month over their entire fertile lifespan. Sequencing of these sperm samples suggests that...
Advances in computational methods are rapidly transforming modern medicine, particularly in safety-critical domains such as anesthesia. In these settings, clinicians must make complex and time-critical decisions, motivating the development of automated and data-driven support systems. A recent study demonstrated the feasibility of reinforcement learning (RL) based propofol infusion control...
We are still actively searching for principles and recipes to design scalable, robust, efficient, and modular microbial bioproduction processes. Engineering natural microbes, however, also means balancing between the interests of the microbe, hardwired in natural biochemistry, and the biotechnologist who aims to upcycle poorly accessible, abundant feedstocks. Could we unlock alternative...
T cells are among the most motile immune cells in the body, and their migration into and within tissues is key to their function. Remarkably, T cells can maintain their motility even in highly crowded environments like the densely packed T cell areas of lymphoid organs, but how they do so remains incompletely understood. In this work\cite{hfsp}, we use microfluidic devices and Cellular Potts...
Regulation of gene expression is essential for organisms to survive and reproduce in fluctuating environments. Machine learning has increasingly been used to understand relationships between non-coding sequences and gene expression. However, most studies rely on data from a limited set of model organisms under controlled laboratory conditions, restricting our understanding of gene regulation...
Traditional analyses of epidemic spreading on networks often rely on spectral properties, steady-state approximations, or aggregate measures of final outbreak size. While these metrics provide essential insights into threshold behaviour, they frequently obscure the granular mechanistic processes by which individual interactions and temporal variations drive population-level dynamics. This work...
Disruption of the microvascular barrier is a hallmark of severe haemorrhagic diseases such as Dengue, while the mechanisms leading to acute vascular leakage and hypovolaemic shock remain incompletely understood. We are developing a cell-based digital twin of 3D microvascular organoid culture systems to investigate how endothelial cells and pericytes self-organise and how this organisation is...
Depolarization block (DB) occurs when strong depolarization prevents neurons from generating action potentials. It is critically involved in several brain disorders, including epilepsy, migraine, and stroke, but also serves physiological roles, for example in odor encoding. Despite the relevance of DB for brain function and dysfunction, relatively few modelling studies directly address its...
There is growing interest in designing microbial communities that perform collective functions, with potential applications ranging from human health to pollutant degradation and crop production. However, attempts to artificially select communities have reported limited success, with modest improvements in performance and a lack of ecological or evolutionary stability.
Here, we approach...
Stochastic version of Susceptible-Infected-Recovered-Vaccinated (SIRV) epidemiological model is observed. The model is constructed from the ordinary differential SIRV model by introducing the additive time-changed Levy noise in the transmission coeffcient. The noise is constructed in terms of a conditional Brownian motion and a doubly stochastic Poisson random field. The structure of these...
DNA methylation is an epigenetic modification in which a methyl group is added to cytosine within CpG dinucleotides. CpG-rich regions are often found in gene promoters and other regulatory elements. Methylation at these loci is a stable, heritable mark that influences transcription, chromatin state, and genome stability [1]. Its dysregulation has been linked to several diseases, including...
Survival analysis is the study of time-to-event data. In a clinical trial, this could be the time to death, or the end of the trial, along with an indicator of whether or not death occurred. Common non- and semi-parametric survival models can only predict survival for at most as long time as a clinical trial is run. Here, we implement survival extrapolation models that extend the survival...
Influenza viruses remain a global health concern; thus, we examine the interplay of host-pathogen interaction using math models. Using human challenge data (Hayden 1999, 2000), we fit our model to analyze the heterogeneity of the observations. We tested hypotheses of immune factors influencing viral kinetics and distinguished the immune components between those who cleared and those who...
Glioblastoma (GBM) creates an immunosuppressive microenvironment that renders current therapies largely ineffective. The STING (Stimulator of Interferon Genes) pathway has emerged as a potent target to remodel this environment and stimulate local immune responses. This study presents a Finite Element Method (FEM) framework to investigate the therapeutic impact of the STING agonist ADU-S100 on...
In cultural evolution, the frequency of a cultural trait often exhibits a nonlinear relationship with its frequency in the previous time step: a trait held by the majority tends to become increasingly common even in the absence of any advantage over the minority trait. This pattern has been attributed to conformist bias, which has been shown to generate a sigmoidal relationship between past...
Inter-individual variability in biological systems is often considered experimental noise, yet its temporal structure can contain valuable information about underlying regulatory mechanisms. Here, we present a stochastic framework that uses fluctuations in cell population dynamics to infer regulatory processes that remain hidden when analyzing only mean behavior. Focusing on adult neural stem...
Active biological systems often operate far from thermodynamic equilibrium, leading to violations of detailed balance and irreversible stochastic dynamics. Red blood cells provide a model system to study nonequilibrium phenomena through membrane flickering, spontaneous fluctuations driven by thermal noise and active intracellular processes. The statistics of these fluctuations reflect the...
In this work, we revisit classical three-dimensional Lotka-Volterra two-
prey-one-predator models with direct prey competition. Employing a rescaling technique, we reduce the system to a simpler model with eight key parameters. With minimal assumptions, all parameters are grouped into four generic categories with a total of nine subcases, which are further refined into 56 sub-items to explore...
In this work, we revisit classical three-dimensional Lotka-Volterra two
prey-one-predator models with direct prey competition. Employing a rescaling technique, we reduce the system to a simpler model with eight key parameters.With minimal assumptions, all parameters are grouped into four generic categories with a total of nine subcases, which are further refined into 56 sub-items to explore...
RNAPolII transcription is a stochastic process where efficiency and fidelity emerge from nonequilibrium dynamics. We present a methodology to quantify the transcriptional efficiency of RNAPII using time series obtained from dual-bead optical tweezers experiments.
Our approach combines stochastic thermodynamics and graph-based time-series analysis. Probability fluxes along the inferred...
The introduction of vaccines during the later phases of the 2019-2022 coronavirus pandemic (COVID-19) emphasized the importance of understanding our immune response and the dynamics of antibody production. We improved a model that previously concentrated on viral replication and T-cells to illustrate the antibody dynamics seen in COVID-19 patients. Our analysis revealed the existence of Hopf...
In many biological and social systems, cooperation depends on collective actions that generate benefits only when a minimal number of individuals coordinate to contribute. These interactions are often modeled using threshold public goods games, in which public goods are produced only if participation exceeds a critical threshold. Cooperative groups vary greatly in size across species, with...
Tertiary lymphoid structures (TLSs) are organised immune aggregates composed of T- and B-cells that form in tumours and are associated with improved patient outcomes. They develop from initially well-mixed lymphocyte populations into spatially organised structures. The mechanisms governing this process remain poorly understood, and there is no clear quantitative framework to relate TLS spatial...
Positive-sense RNA viruses employ various strategies to suppress host immune defenses. Understanding the dynamic interaction between the viral life cycle and immune signaling is crucial for designing effective antiviral strategies. Here, we develop a mathematical model integrating the intracellular viral life cycle with key innate immune pathways, including RIG-I-mediated detection and...
Tumour growth and treatment response emerge from coupled interactions between mechanics, hypoxia, and drug transport, yet most phase-field models remain purely forward with fixed parameters. This limits their ability to capture tumour-specific variability.
We develop a mechanochemically coupled phase-field model integrating tumour evolution, oxygen dynamics, paclitaxel transport, and...
Ladderpath is a compression-based framework, grounded in Algorithmic Information Theory, for extracting repeated, nested, and hierarchically organized structure from symbolic sequences. Rather than treating biological sequences as flat strings, it reconstructs reusable building blocks and their dependency relations, yielding interpretable representations together with quantitative measures of...
Ordinary differential equation models are central to systems biology and computational biology because they provide interpretable descriptions of regulatory, signaling and population-level dynamics \cite{ma}.
In many biological applications, however, longitudinal data are sparse, noisy, irregularly sampled and heterogeneous across individuals or experimental units. Classical nonlinear...
Infectious disease forecasting in novel outbreaks or low-resource settings is hampered by the need for large disease and covariate datasets, bespoke training, and expert tuning, all of which can hinder rapid generation of forecasts for new settings. To address these challenges, we developed Mantis, a foundation model trained entirely on mechanistic simulations, which enables out-of-the-box...
The immune system can eradicate cancer, but various immunosuppressive mechanisms active within a tumor curb this beneficial response. Unraveling the effects of multimodal interactions between tumor and immune cells and their contributions to tumor control using an experimental approach alone is time- and resource-intensive. To identify key immunological features associated with tumor control...
Heart failure with preserved ejection fraction (HFpEF) is growing in prevalence, often attributed to an ageing and obese population. It lacks effective treatments due to poorly understood pathophysiology and absence of translationally relevant animal models \cite{gao_animal_2024}. The aim of this work is to couple an in vitro system of strip-based engineered heart tissue (EHT) with a...
An alternative to daily or on-demand methods (pills/gels), intravaginal rings (IVRs) provide long-term, topical drug delivery for contraception, HIV prophylaxis, and hormone therapy. Current IVR designs are based on empirical interpretations of in vitro and in vivo experiments in animals and humans. We developed a deterministic mathematical model of IVR-based drug delivery, to enhance rational...
Drug delivery in solid tumors is a major challenge due to the complex tumor microenvironment. Abnormal vasculature, a dense extracellular matrix (ECM), and elevated interstitial fluid pressure (IFP) hinder the penetration of therapeutic agents [1]. ECM-modifying therapies have been proposed to overcome these barriers by altering the structure of the ECM and improving drug transport in tumor...
We develop mathematical models to study the role of mechanical forces in determining plant cell and tissue polarity. Our focus lies on SOSEKI proteins (SOKs) that distribute anisotropically along the cell membrane. Recent work suggests that SOKs are mechanosensitive \cite{p}, creating a potential connection between mechanics and plant cell polarity essential to plant organ development.
The...
Ovarian epithelial cancer still claims the highest mortality rates of all \nobreakdash{gynaecological}
cancers to date, in part due to its complex tumour immune microenvironment (TIME) \cite{Veneziani2023}. The lymphocyte $\gamma\delta$ T cell subset has emerged as a promising target in cancer-related disease, such as ovarian carcinoma, due to its immunological plasticity...
Parkinson's disease (PD) is a progressive neurodegenerative disorder whose underlying molecular mechanisms remain poorly understood, hindering development of targeted therapeutics. While 10% of cases are linked to mutations in over 20 genes, the majority are idiopathic, reflecting the disease's complexity. Recent approaches use multi-OMICS characterization of patient-derived neurons obtained...
Computational, data-driven predictors of protein-protein interactions have become an active research area in interaction proteomics. Interestingly, high-performing baseline sequence-based models designed to predict interacting protein pairs were recently found to be trained on datasets of high similarity, resulting in data leakage during model training. In this study, we analyze...
Bacteria interact in different ways, from competition to cooperation, depending on resource availability in the environment.
Identifying environments that foster these dynamics is both important and challenging, as the outcomes often depend on subtle alignment between the dynamic metabolic needs of species.
A common community approach to this challenge has been metabolic...
The brain critically depends on a continuous vascular supply of oxygen and glucose. Cerebral blood flow is locally regulated by neuronal activity through neurovascular coupling (NVC), a mechanism that optimizes energy delivery to active brain regions via coordinated vasodilation and vasoconstriction. NVC arises from interactions between neurons, astrocytes, and blood vessels. While...
We present an open-source computational framework for the numerical solution of mechanochemical continuum models based on viscoelastic mechanics, with optional coupling to reaction-diffusion-advection dynamics of biochemical species. The framework is implemented in Python and adopts a method-of-lines formulation: spatial derivatives are discretised using finite-difference schemes, transforming...
The adoption of artificial intelligence in healthcare is increasing rapidly, yet only a small number of applications have reached routine clinical use. A central obstacle is the lack of transparency, as many machine learning models operate as black boxes that produce predictions without interpretable reasoning. This contribution explores an alternative approach based on geometric data...
Biological pattern formation is often based on non-linear interactions of chemicals and their movement, and reaction-diffusion models are a classic theoretical framework for explaining such patterning. A good example is seen in the root of Arabidopsis thaliana, where each cell commits to one of two fates: trichoblast and atrichoblast. Experimental data reveal a puzzling phenomenon in this...
Smallpox, caused by the variola viruses, led to high mortality throughout human history. Although eradicated, virus samples are held in laboratories and accidental or deliberate release remains possible. Many countries therefore maintain smallpox vaccine stockpiles as part of preparedness planning.
Historically, vaccination strategies were constrained by the risks associated with first...
Prostate cancer (PCa) has been widely studied, yet new strategies are needed to mitigate resistance and recurrence. Ferroptosis, an iron-dependent form of regulated cell death, is emerging as a promising therapeutic strategy, yet its mathematical modelling in PCa remains limited \cite{Maccarinelli2023}. This is especially relevant for castration-resistant prostate cancer (CRPC), where hormonal...
Chronic inflammatory disorders, such as inflammatory bowel disease (IBD), are characterized by unpredictable transitions between disease remission and debilitating flare-ups driven by gut dysbiosis. Despite extensive research, the mechanistic drivers of these relapse-remission cycles and the optimal strategies to restore stability remain elusive. Here, we introduce a minimal mechanistic...
It is intuitive that stirring homogenizes and increases the efficiency of liquid chemical reactions. However, in complex nonlinear systems, stirring can also alter intrinsic dynamics. Such systems may show bistability, excitability, or periodicity. A prominent example is the Belousov-Zhabotinsky reaction, where stirring effects have long been studied...
Recent experiments show that cannibalism in predators and de-
fense in prey can both occur concurrently. Motivated by this, we investigate
a predator-prey system where cannibalism occurs in predators and defense in
prey simultaneously. System analysis show that depending on the prey defense
(µ) and predator cannibalism (c) parameters respectively, one can have global
stability of the...
This study numerically investigates optimal intervention strategies for reducing overweight and obesity using a compartmental dynamical model with three classes: normal-weight, overweight, and obese individuals. Two time-dependent controls are considered: a preventive strategy promoting healthy lifestyles and a treatment intervention targeting obese individuals. The optimal control problem is...
High-grade serous ovarian cancer (HGSOC) is the leading cause of gynecologic cancer mortality. Late diagnosis, widespread disease, and frequent relapse limit the effectiveness of current therapies. p53 deficiency indicates HGSOCs are vulnerable to cell-cycle inhibitors; however, currently available agents have shown less clinical benefit than expected. We hypothesize that maximizing the...
In 2024, Brazil faced its worst dengue epidemic, with 6 million cases and 5,000 deaths. A shift toward higher mortality among the elderly challenges WHO strategies prioritizing children. As immunity varies across Brazil’s geography, a "one-size-fits-all" vaccination approach may not be optimal.
We reconstructed state- and age-specific immune profiles across Brazil by fitting an age-structured...
Enzyme inhibition analysis is essential in drug development and food processing, necessitating precise estimation of inhibition constants. Traditionally, these constants are estimated through experiments using multiple substrate and inhibitor concentrations, but inconsistencies across studies highlight a need for a more systematic approach to set experimental designs across all types of enzyme...
Propofol anesthesia reshapes electroencephalogram (EEG) dynamics, producing prominent slow-delta and alpha oscillations, see \cite{Purdon15}. Biophysical models provide a mechanistic framework for understanding how these rhythms emerge from neuronal interactions. In this work, we implement the biophysical thalamocortical network model of Soplata et al. \cite{Soplata23}, which describes...
In the field of structure-based drug design, there is enormous interest in determining the binding characteristics and physical orientations of putative therapeutic ligands within the binding sites of the proteins they target. A primary tool to investigate this binding interaction involves characterizing the structure of the protein bound to its ligand, typically using X-ray crystallography...
Mathematical models can be used in order to verify medical hypotheses and quantify the mechanisms of the progression of neurological pathologies like Alzheimer's disease. Here we consider a model based on ordinary differential equations incorporating dynamics of toxic proteins like Amyloid $\beta$ species and tau tangles and describing their spread on a brain graph based on the human...
Accurate assessment of the infection scale is essential for determining the end of Ebola virus disease (EVD) outbreaks in West Africa. Previous compartmental modeling studies often assume the total population to be the effective population size or simply preset the initial number of infections. These simplifying assumptions can distort transmission dynamics and reduce prediction...
Spatial accessibility to healthcare can influence population health outcomes during large-scale public health crises. However, its contribution to excess mortality beyond directly reported COVID-19 deaths remains insufficiently quantified. This study evaluates the relationship between regional healthcare accessibility and excess mortality across South Korea during the COVID-19...
Heavy menstrual bleeding (HMB) is linked to dysregulated inflammatory signaling and abnormal spiral artery function. However, the mechanism connecting endometrial inflammation and vascular response is not well understood. To address this, we are extending an existing mechanistic ordinary differential equation model of the menstrual cycle. Our expanded framework incorporates the inflammatory...
COVID-19 epidemics have repeatedly coincided with shifts in dominant variants, and summer hospitalization increases were observed in South Korea in 2024 and 2025. This study aims to quantitatively evaluate and forecast the impact of dominant variant transition on the scale of the 2026 summer epidemic in South Korea.
Hospitalization surveillance and SARS-CoV-2 sequence data from January 1,...
Calcium-induced calcium release plays a significant role in mammalian skeletal and cardiac cell excitation. The ion channels responsible for this process are called ryanodine receptors (RyRs), which can exist in several conformational states, including open, closed and inactivated. Transitions between these states are regulated by concentrations of ligands, particularly calcium and magnesium....
The growing prevalence of antibiotic-resistant bacteria poses a major global health challenge. Pseudomonas aeruginosa, identified by the WHO as a critical antibiotic-resistant pathogen, highlights the need for alternative therapies. Because iron is essential for bacterial survival and is often acquired through siderophores, disrupting iron uptake, particularly through interactions with...
In Spring 2025, a foot-and-mouth disease (FMD) outbreak occurred along the Hungary-Slovakia border region, affecting 11 farms before being contained. While the small number of cases is encouraging from a control perspective, it poses a major statistical challenge: standard methods for inferring transmission parameters and evaluating control measures are not suitable for such limited data....
Consumer-grade wearables enables continuous monitoring and early detection of aberrant physiological signals associated with diverse health issues. However, substantial measurement noise and natural physiological variability in wearable data have prevented reliable identification of physiological anomalies, limiting their deployment in real-world and clinical settings. Here, we propose a...
Influenza is a seasonal infectious disease, and real-time forecasting of outbreaks is essential for effective public health responses. In Korea, influenza surveillance relies on two types of data. Influenza-Like Illness (ILI) data collected through sentinel surveillance reflects outbreak trends, whereas confirmed case data obtained through universal surveillance better represent the total...
Nosocomial infections, also known as hospital-acquired infections, pose a major public health challenge, particularly due to the increase of antibiotic-resistant pathogens.\cite{edman_2025} Understanding how such infections spread within hospitals is vital for effective infection control.
Outbreak reconstruction, to infer the underlying transmission tree based on observed data, is of...
Patient monitoring after radiotherapy for prostate cancer relies on population-based thresholds of rising prostate-specific antigen (PSA), ignoring patient-specific tumor dynamics and uncertainty. To avoid delays in recurrence detection and treatment, we propose a personalized Bayesian mechanistic framework to forecast post-radiotherapy PSA dynamics. These forecasts enable the definition of...
The Wright-Fisher (W-F) diffusion model is a foundational framework for understanding allele frequency dynamics.
In \cite{roa2024} an exact analytical expression for the transition density strictly within the open interval (0, 1) is derived for the W-F model without mutation.
In this work, we introduce mutation, changing the nature of the barriers 0 and 1 from absorbing states to a...
Observing the decisions and actions of others within a group (such as running from a predator) provides social information that can inform actions such as whether to follow. We consider a model where all agents simultaneously gather stochastic private information (weighted towards an unknown preference), coming to a decision once sufficiently confident. These observing agents infer the state...
Neurons are specialized cells which transmit signals and move biological material across their axons and dendrites. The fundamental organization of neurons relies on microtubules (MTs) which are elongated protein polymers with a plus and minus end. These MTs form tracks on which cargo can be transported within the cell. It is well known that dendritic MTs are extremely dynamic, reorganize...
We present corrosive-passivating models to describe the initiation of corrosion patterns on metal surfaces, particularly fuel tank bottoms. The classical Barkley model for excitable systems [1] has been also applied in the context of corrosion [2], modeling the interaction between corrosive and passivating species as a fast activator and a slow inhibitor, respectively. However, the original...
The bacterium Coxiella burnetii is the causative agent of Q-Fever. Inhalation of a small number of bacteria in the dormant form is sufficient to cause disease. Following exposure, alveolar macrophages host both the morphological switching to a replicative variant, and bacterial proliferation. Upon host cell death, the intracellular population of C. burnetii is released and can propagate...
Dynamical systems in biochemistry are complex, and one often does not have comprehensive knowledge about the interactions involved. Chemical reaction network (CRN) inference aims to identify, from observing time-series of species concentrations, the unknown reactions between the species. Most frequentist approaches to CRN inference focus on identifying a single, most likely CRN, without...
Self-report questionnaires are widely used in healthcare to assess disease risk and symptom severity. However, their length can burden respondents and compromise data quality. While machine learning models have enabled the development of shortened questionnaires with high predictive performance, they often operate as black boxes, limiting transparency and requiring specialized expertise that...
Black Sigatoka disease is an airborne fungal infection caused by \textit{Pseudocercospora fijiensis} that severely impacts global banana and plantain production. Its persistence and resistance to eradication make it one of the most challenging plant diseases to manage. We develop a deterministic host–pathogen model that captures BSD dynamics through dual transmission pathways and mate...
Maintaining a stable oxygen supply to the brain is essential to meet its high metabolic demands and sustain cognitive function. Assessing how microvascular changes affect cerebral energy supply is challenging due to complex capillary networks and small-scale vascular alterations. To address this, we developed a computational model of oxygen transport incorporating microvascular perfusion...
Actin assembly drives force generation and membrane remodelling (protrusion, budding, tethering). Many actin kinetic models omit explicit energy accounting with force production \cite{Vavylonis2005,Ditlev2009}, limiting reliable coupling to multiscale models of cell remodelling. Prior efforts linking actin kinetics to continuum mechanics often approximate energy flows and omit explicit...
Spatial transcriptomics studies are becoming increasingly large and commonplace, necessitating the simultaneous analysis of a large number of spatially resolved variables. Correspondingly, a diverse range of methodologies have been proposed to compare the spatial expression structure of genes. Here we apply persistent homology, a method from topological data analysis, to produce a continuous...
This study investigates a predator–prey system incorporating a transmissible disease that spreads exclusively within the prey population and intraspecific competition among predators. The dynamics are modeled using a system of reaction–diffusion equations to account for both local interactions and spatial movement. In this system, we focus on the occurrence of diffusion-driven instability, or...
Tuberculosis (TB) remains a worldwide health challenge. Adherence to TB treatment is usually compromised due to patients' concerns related to social stigma, economic constraints, and the demanding nature of long and closely monitored treatment regimens. This study introduces a novel Susceptible-Latent-Infected-Treated-Recovered-Failed (SLITRF) compartmental model that integrates dynamic game...
