Dynamic signalling
ODE-based representations of phosphorylation, regulatory networks and time-resolved molecular responses.
Computational Systems Biologist
Mechanistic models and scientific software for signalling dynamics, multi-omics and drug response.
I combine mathematical modelling, optimization, Bayesian inference and reproducible scientific computing to study dynamic biological systems, particularly cancer signalling, treatment response and pharmacological processes.
Research focus
ODE-based representations of phosphorylation, regulatory networks and time-resolved molecular responses.
Mechanistic models of treatment response, pharmacokinetics and coupled biological dynamics.
Optimization and Bayesian approaches for extracting dynamic structure from proteomic and molecular measurements.
Testable packages, interoperable models and portable workflows that make computational analyses reusable.
Questions driving my research
Selected work
Mechanistic framework for reconstructing phosphorylation dynamics from time-resolved molecular measurements and kinase–substrate networks using ODE models, constrained optimization and sensitivity analysis.
Methods ODE modelling · constrained optimization · sensitivity analysis
Systems-level phospho-network modelling that integrates post-translational crosstalk, kinase–substrate networks and phosphosite time series with multi-objective evolutionary optimization.
Methods ODE networks · PTM crosstalk · multi-objective optimization
SBML-based ordinary differential equation model of tirzepatide absorption, distribution and elimination, developed as a reproducible pharmacokinetic modelling study.
Methods PBPK · ODEs · SBML · parameter estimation
JAX-based simulation of a non-isothermal Allen–Cahn tumour-growth model coupling cell, temperature and nutrient dynamics with spectral or finite-difference solvers.
Methods PDEs · JAX · spectral methods · finite differences
Working approach