23 papers · ranked by Valyu relevance
Authors not listed
Deriving versatile and robust mechanistic models from experimental data is a key challenge in engineering and natural sciences. This is especially true in chemical reaction engineering, where reactor manufacturers and operators increasingly pursue the development and maintenance of digital twins that rely on frequent…
Nikola Simidjievski, Ljupčo Todorovski, Juš Kocijan, Sašo Džeroski
—Equation discovery methods enable modelers to combine domain-specific knowledge and system identification to construct models most suitable for a selected modeling task. The method described and evaluated in this paper can be used as a nonlinear system identification method for gray-box modeling. It consists of two…
O. Ebenhöh, M. van Aalst, N.P. Saadat, T. Nies + 1 more
The modelbase package is a free expandable Python package for building and analysing dynamic mathematical models of biological systems. Originally it was designed for the simulation of metabolic systems, but it can be used for virtually any deterministic chemical processes. modelbase provides easy construction methods…
John T. Nardini, Ruth E. Baker, Matthew J. Simpson, Kevin Flores
Agent-based models provide a flexible framework that is frequently used for modelling many biological systems, including cell migration, molecular dynamics, ecology, and epidemiology. Analysis of the model dynamics can be challenging due to their inherent stochasticity and heavy computational requirements. Common…
Marvin van Aalst, Oliver Ebenhöh, Anna Matuszyńska
Computational mathematical models of biological and biomedical systems have been successfully applied to advance our understanding of various regulatory processes, metabolic fluxes, effects of drug therapies and disease evolution or transmission. Unfortunately, despite community efforts leading to the development of…
Jovan Tanevski, Ljupčo Todorovski, Sašo Džeroski
Background Identifying a proper model structure, using methods that address both structural and parameter uncertainty, is a crucial problem within the systems approach to biology. And yet, it has a marginal presence in the recent literature. While many existing approaches integrate methods for simulation and parameter…
Marvin van Aalst, Oliver Ebenhöh, Anna Matuszyńska
Background Computational mathematical models of biological and biomedical systems have been successfully applied to advance our understanding of various regulatory processes, metabolic fluxes, effects of drug therapies, and disease evolution and transmission. Unfortunately, despite community efforts leading to the…
Alan Veliz-Cuba, Stephen Randal Voss, David Murrugarra
A primary challenge in building predictive models from temporal data is selecting the appropriate network and the regulatory functions that describe the data. Software packages are available for equation learning of continuous models, but not for discrete models. In this paper we introduce a method for building model…
Authors not listed
Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture…
Da Li, Junping Yin, Jin Xu, Xinxin Li + 1 more
c Symbolic regression automatically searches for mathematical equations to reveal underlying mechanisms within datasets, offering enhanced interpretability compared to black box models. Traditionally, symbolic regression has been considered to be purely numeric-driven, with insufficient attention given to the potential…
Franziska Taeger, Lena Mende, Steffen Fleßa
Different types of mathematical models can be used to forecast the development of diseases as well as associated costs and analyse the cost-effectiveness of interventions. The set of models available to assess these parameters, reach from simple independent equations to highly complex agent-based simulations. For many…
Søren Saxmose Nielsen, Julio Alvarez, Paolo Calistri, Elisabetta Canali + 18 more
'Elisabetta Canali' 'Julian Ashley Drewe' 'Bruno Garin‐Bastuji' 'José Luis Gonzales Rojas' 'Christian Gortázar' 'Mette Herskin' 'Virginie Michel' 'Miguel Ángel Miranda Chueca' 'Barbara Padalino' 'Paolo Pasquali' 'Helen Clare Roberts' 'Hans Spoolder' 'Karl Ståhl' 'Antonio Velarde' 'Arvo Viltrop' 'Christoph Winckler'…
Valentinus Vidia Galih Putra, Juliany Ningsih Mohamad
The application of differential equations is commonly used in mathematics and physics, as well as various other sciences to explain a phenomenon in a system. This paper explains the mathematical modeling in the analysis of the nCOVID-19 plague in Indonesia on March 3, 2020, to April 19, 2020, with the modification of…
Authors not listed
This paper presents the Multi Cell-line Kinetic Model (MCKM), a novel generalised kinetic mechanistic model specifically tailored for Ambr15™ fed-batch cultivations of multiple Chinese Hamster Ovary (CHO) cell lines producing different recombinant monoclonal antibodies (mAbs). Unlike traditional models that requires…
Edmund Jones, David Epstein, Leticia García-Mochón
For health-economic analyses that use multistate Markov models, it is often necessary to convert from transition rates to transition probabilities, and for probabilistic sensitivity analysis and other purposes it is useful to have explicit algebraic formulas for these conversions, to avoid having to resort to numerical…
Petr Kuzmic
The mathematics and geometry of the "kobs" method under the tight-binding experimental conditions, when inhibitor depletion is significant, has not been fully explored in the existing biochemical kinetic literature. It is shown here that under tight-binding conditions a plot of the pseudo-first order rate constant…
Christopher Schölzel, Valeria Blesius, Gernot Ernst, Andreas Dominik
Reproducible, understandable models that can be reused and combined to true multi-scale systems are required to solve the present and future challenges of systems biology. However, many mathematical models are still built for a single purpose and reusing them in a different context can be challenging due to an…
Authors not listed
In this work, we present EquiNet, a neural network for predicting vapor–liquid equilibrium (VLE) in novel binary mixtures through direct estimation of activity coefficients and vapor pressures. The model embeds a classic excess-Gibbs free energy formulation, ensuring Gibbs–Duhem consistency on all predicted activity…
Klaus‐Dieter Sommer, P M Harris, Sascha Eichstädt, Roland Füßl + 9 more
'Tanja Dorst' 'Andreas Schütze' 'Michael Heizmann' 'Nadine Schiering' 'Andreas Maier' 'Yuhui Luo' 'Christos Tachtatzis' 'Ivan Andonović' 'Gordon Gourlay'] - 1 Technische Universitaet Ilmenau, Germany - 2 National Physical Laboratory, Teddington, United Kingdom - 3 Physikalisch-Technische Bundesanstalt, Braunschweig and…
Authors not listed
Inverse problems, where we seek the values of inputs to a model that lead to a desired set of outputs, are a challenges subset of problems in science and engineering. In this work we demonstrate the use of two generative AI methods to solve inverse problems. We compare this approach to two more conventional approaches…
Teegwendé V. Porgo, Susan L. Norris, Georgia Salanti, Leigh F. Johnson + 4 more
'Leigh F. Johnson' 'Julie A. Simpson' 'Nicola Low' 'Matthias Egger' 'Christian L. Althaus'] Mathematical modeling studies are increasingly recognised as an important tool for evidence synthesis and to inform clinical and public health decision-making, particularly when data from systematic reviews of primary studies do…
Kate E. Dray, Joseph J. Muldoon, Niall M. Mangan, Neda Bagheri + 1 more
Mathematical modeling is invaluable for advancing understanding and design of synthetic biological systems. However, the model development process is complicated and often unintuitive, requiring iteration on various computational tasks and comparisons with experimental data. Ad hoc model development can pose a barrier…
Authors not listed
Phase equilibrium calculations are crucial in chemical engineering design and optimization processes. The PC-SAFT equation of state (EoS) can precisely calculate phase equilibrium, but is relatively complex and computationally intensive. Surrogate models are mathematically simple models that map or regress the…