Model-based design of experiments for parameter precision: State of the art

G Franceschini, S Macchietto - Chemical Engineering Science, 2008 - Elsevier
Due to the wide use and key importance of mathematical models in process engineering,
experiment design is becoming an essential tool for the rapid building and validation of …

Systems biology—an engineering perspective

A Kremling, J Saez-Rodriguez - Journal of biotechnology, 2007 - Elsevier
The interdisciplinary field of systems biology has evolved rapidly over the last years.
Different disciplines have aided the development of both its experimental and theoretical …

Exploiting the bootstrap method for quantifying parameter confidence intervals in dynamical systems

M Joshi, A Seidel-Morgenstern, A Kremling - Metabolic engineering, 2006 - Elsevier
A quantitative description of dynamical systems requires the estimation of uncertain kinetic
parameters and an analysis of their precision. A method frequently used to describe the …

Sloppy models, parameter uncertainty, and the role of experimental design

JF Apgar, DK Witmer, FM White, B Tidor - Molecular BioSystems, 2010 - pubs.rsc.org
Computational models are increasingly used to understand and predict complex biological
phenomena. These models contain many unknown parameters, at least some of which are …

Iterative approach to model identification of biological networks

KG Gadkar, R Gunawan, FJ Doyle - BMC bioinformatics, 2005 - Springer
Background Recent advances in molecular biology techniques provide an opportunity for
developing detailed mathematical models of biological processes. An iterative scheme is …

A benchmark for methods in reverse engineering and model discrimination: problem formulation and solutions

A Kremling, S Fischer, K Gadkar, FJ Doyle… - Genome …, 2004 - genome.cshlp.org
A benchmark problem is described for the reconstruction and analysis of biochemical
networks given sampled experimental data. The growth of the organisms is described in a …

When physics-informed data analytics outperforms black-box machine learning: A case study in thickness control for additive manufacturing

K Wang, M Zeng, J Wang, W Shang, Y Zhang… - Digital Chemical …, 2023 - Elsevier
Aerosol jet printing (AJP) has emerged as a promising noncontact additive manufacturing
method for high-resolution printing for a wide range of material systems. A key challenge …

Model-based design of parallel experiments

F Galvanin, S Macchietto, F Bezzo - Industrial & engineering …, 2007 - ACS Publications
Advanced model-based experiment design techniques are essential for the rapid
development, refinement, and statistical assessment of deterministic process models. One …

On validation and invalidation of biological models

J Anderson, A Papachristodoulou - BMC bioinformatics, 2009 - Springer
Background Very frequently the same biological system is described by several, sometimes
competing mathematical models. This usually creates confusion around their validity, ie …

Experiment selection for the discrimination of semi-quantitative models of dynamical systems

I Vatcheva, H De Jong, O Bernard, NJI Mars - Artificial Intelligence, 2006 - Elsevier
Modeling an experimental system often results in a number of alternative models that are all
justified by the available experimental data. To discriminate among these models, additional …