Fitting thermodynamic-based models: incorporating parameter sensitivity improves the performance of an evolutionary algorithm

DOI10.1016/j.mbs.2021.108716zbMath1480.92073OpenAlexW3210786298MaRDI QIDQ2066475

Michael J. Gaiewski, Jacqueline M. Dresch, Robert A. Drewell

Publication date: 14 January 2022

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mbs.2021.108716

zbMATH Keywords

parameter estimationsensitivity analysisevolutionary algorithmtranscriptionthermodynamic-based model

Mathematics Subject Classification ID

Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Biochemistry, molecular biology (92C40)

Uses Software

• Matlab
• SIGOA
• Optimization Toolbox

Cites Work

• A methodology for performing global uncertainty and sensitivity analysis in systems biology
• GpoSolver: a Matlab/C++ toolbox for global polynomial optimization
• Two-Layer Mathematical Modeling of Gene Expression: Incorporating DNA-Level Information and System Dynamics
• Advances in Artificial Intelligence – SBIA 2004

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