Comparing AI versus Optimization Workflows for Simulation-Based Inference of Spatial-Stochastic Systems

MA Ramirez Sierra, T Sokolowski - Machine Learning: Science …, 2024 - iopscience.iop.org
Abstract Model parameter inference is a universal problem across science. This challenge is
particularly pronounced in developmental biology, where faithful mechanistic descriptions …

Quantifying Parameter Interdependence in Stochastic Discrete Models of Biochemical Systems

S Gholami, S Ilie - Entropy, 2023 - mdpi.com
Stochastic modeling of biochemical processes at the cellular level has been the subject of
intense research in recent years. The Chemical Master Equation is a broadly utilized …

AI-powered simulation-based inference of a genuinely spatial-stochastic gene regulation model of early mouse embryogenesis

MA Ramirez Sierra, TR Sokolowski - PLOS Computational Biology, 2024 - journals.plos.org
Understanding how multicellular organisms reliably orchestrate cell-fate decisions is a
central challenge in developmental biology, particularly in early mammalian development …

[HTML][HTML] Efficient Finite-Difference Estimation of Second-Order Parametric Sensitivities for Stochastic Discrete Biochemical Systems

F Jabeen, S Ilie - Mathematical and Computational Applications, 2024 - mdpi.com
Biochemical reaction systems in a cell exhibit stochastic behaviour, owing to the
unpredictable nature of the molecular interactions. The fluctuations at the molecular level …

AI-powered simulation-based inference of a genuinely spatial-stochastic model of early mouse embryogenesis

MA Ramirez-Sierra, TR Sokolowski - arXiv preprint arXiv:2402.15330, 2024 - arxiv.org
Understanding how multicellular organisms reliably orchestrate cell-fate decisions is a
central challenge in developmental biology. This is particularly intriguing in early …