58 citations · 73 across the 4 of their papers we have counts for
7 papers
CoODE: Conditionally Coarse-Grained Model Discovery for Rewiring in Biochemical Networks
Theodore de Pomereu, Fabian Fröhlich
Biochemical networks propagate the signals that regulate cellular behaviour, and which routes carry them depends on cellular context: a shift in context rewires the network's effec…
PEtab SciML: an exchange format for specifying and training dynamic scientific machine learning models
Sebastian Persson, Branwen Snelling, Maren Philipps +5
Summary: Dynamic scientific machine learning (SciML) models that combine mechanistic ordinary differential equations (ODEs) with machine learning (ML) components have applications…
Curriculum Multiple Shooting for Robust Training of Neural and Universal Differential Equations
Sebastian Persson, Giacomo Fabrini, Branwen Snelling +1
Neural ordinary differential equations (NODEs) and universal differential equations (UDEs) provide flexible and popular frameworks for learning interpretable dynamical systems from…
pyPESTO: A modular and scalable tool for parameter estimation for dynamic models
Yannik Schälte, Fabian Fröhlich, Paul J. Jost +14
Mechanistic models are important tools to describe and understand biological processes. However, they typically rely on unknown parameters, the estimation of which can be challengi…
A protocol for dynamic model calibration
Alejandro F. Villaverde, Dilan Pathirana, Fabian Fröhlich +2
Ordinary differential equation models are nowadays widely used for the mechanistic description of biological processes and their temporal evolution. These models typically have man…
AMICI: High-Performance Sensitivity Analysis for Large Ordinary Differential Equation Models
Fabian Fröhlich, Daniel Weindl, Yannik Schälte +5
Ordinary differential equation models facilitate the understanding of cellular signal transduction and other biological processes. However, for large and comprehensive models, the…
Scalable Inference of Ordinary Differential Equation Models of Biochemical Processes
Fabian Fröhlich, Carolin Loos, Jan Hasenauer
Ordinary differential equation models have become a standard tool for the mechanistic description of biochemical processes. If parameters are inferred from experimental data, such…