23 papers · ranked by Valyu relevance
Agus Hasan
Title: Graphical abstract
Abid Hossain Khan, Salauddin Omar, Nadia Mushtary, Richa Verma + 2 more
'Dinesh Kumar' 'Syed Bahauddin Alam'] Surrogate modeling has brought about a revolution in computation in the branches of science and engineering. Backed by Artificial Intelligence, a surrogate model can present highly accurate results with a significant reduction in computation time than computer simulation of actual…
Hyeseon Jeon, Woojin Jung, Hwi-yeol Yun, Soyoung Lee + 3 more
Target-mediated drug disposition (TMDD) models have been widely used to describe nonlinear pharmacokinetic profiles driven by high-affinity, low-capacity drug–target binding. A pTMDD model, derived by applying the Padé approximation of the quasi-steady-state (QSS) model (qTMDD) was previously proposed. Although pTMDD…
Sabyasachi Shivkumar, Madeline S. Cappelloni, Ross K. Maddox, Ralf M. Haefner
Perceptual decision-making has been extensively modeled using the ideal observer framework. However, a range of deviations from optimality demand an extension of this framework to characterize the different sources of suboptimality. Prior work has mostly formalized these sources by adding biases and variability in the…
Evan Taylor, Edward J. Louis, Gregory Mocko
Digital engineering has transformed the design and development process. However, the utility of digital engineering is fundamentally dependent on the assumption that a simulation provides information consistent with reality. This relationship is described as model fidelity. Despite the widespread use of the term…
Begoña Ispizua, Josu Doncel, Jalel Ben-Othman
Mean-field approximation is a method to investigate the behavior of stochastic models formed by a large number of interacting objects. A new approximation was recently established, i.e., the refined mean-field approximation, and its high accuracy when the number of objects is small has been shown. In this work, we…
Jun Lu, Yudong Fang, Weijian Han, Yan Wang
Surrogate models are commonly used as a substitute for the computation-intensive simulations in design optimization. However, building a high-accuracy surrogate model with limited samples remains a challenging task. In this paper, a novel adaptive-weight ensemble surrogate modeling method is proposed to address this…
Luis L. Fonseca, Lucas Böttcher, Borna Mehrad, Reinhard C. Laubenbacher + 1 more
'Reinhard C. Laubenbacher' 'Mark Alber'] This paper describes and validates an algorithm to solve optimal control problems for agent-based models (ABMs). For a given ABM and a given optimal control problem, the algorithm derives a surrogate model, typically lower-dimensional, in the form of a system of ordinary…
Sam Motsoka Rametse, Sheldon Herbst
Accurate and stable numerical simulation of epidemic dynamics is essential for translating mathematical models into reliable computational tools for public health. The Susceptible–Infectious–Recovered (SIR) model remains a cornerstone of mathematical epidemiology, yet the robustness of its numerical treatment strongly…
Zhixiao Zhu, Maria Christodoulou, David Steinsaltz
Many complex systems are modelled using modular models, where individual sub-models are estimated separately and then combined. While this simplifies inference, it fails to account for interactions between components. A natural solution is to estimate all components jointly, but this is often impractical due to…
Maurice HT Ling
Modeling and simulation are recognized as important aspects of the scientific method for more than 70 years but its adoption in biology has been slow. Debates on its representativeness, usefulness, and whether the effort spent on such endeavors is worthwhile, exist to this day. Here, I argue that most of learning is…
Luke Allan, Tim Zuehlsdorff
The second order cumulant method offers a promising pathway to predicting optical properties in condensed phase systems. It allows for the computation of linear absorption spectra from excitation energy fluctuations sampled along molecular dynamics (MD) trajectories, fully accounting for vibronic effects, direct…
Authors not listed
Model Hamiltonians represent a convenient way of reducing complex problems of many-electron quantum mechanics to much simpler problems: they can fully reproduce the core behaviors of a system of interest by encoding only the dominant physical interactions and using only a small number of associated parameters. Model…
Chenxi Wang, Jihui Zhao, Jingjing Zheng, Barak Raveh + 2 more
Developing and optimizing models for complex systems poses challenges due to the inherent complexity introduced by multiple types of input information and sources of uncertainty. In this study, we utilize Bayesian formalism to analytically examine the propagation of probability in the modeling process and propose…
Robert Arbon, Yanchen Zhu, Antonia S. J. S. Mey
Markov state models (MSM) are a popular statistical method for analyzing the conformational dynamics of proteins, including protein folding. With all statistical and machine learning (ML) models choices must be made about the modeling pipeline that cannot be directly learned from the data. These choices, or…
Beatrix C. Hiesmayr, Marc‐Thorsten Hütt
A recent trend in mathematical modeling is to publish the computer code together with the research findings. Here we explore the formal question, whether and in which sense a computer implementation is distinct from the mathematical model. We argue that, despite the convenience of implemented models, a set of implicit…
Conrad Hübler
A novel application to determine stability constants from supramolecular titration experiments is presented. The focus lies on NMR titration and ITC experiments for pure 1:1 systems, as well as mixed 2:1/1:1, 1:1/1:2 and 2:1/1:1/1:2 systems. SupraFit provides global and local fitting and a global search tool.…
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'…
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
Hydration free energy (HFE) of molecules is a fundamental property having impor- tance throughout chemistry and biology. Calculation of the HFE can be challenging and expensive with classical molecular dynamics simulation-based approaches. Ma- chine learning (ML) models are increasingly being used to predict HFE.…
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…
Authors not listed
Kinetic modeling is essential for predicting changes in food quality during processing and storage. This study evaluates the application of physics-informed neural networks (PINN) for food kinetic modeling, integrating kinetic insights into neural network frameworks. Based on three case studies, namely seed drying…
Andrey A. Toropov, Alla P. Toropova, Alessandra Roncaglioni, Emilio Benfenati + 3 more
'Emilio Benfenati' 'Danuta Leszczynska' 'Jerzy Leszczynski' 'Marzio Rosi'] Data on Henry’s law constants make it possible to systematize geochemical conditions affecting atmosphere status and consequently triggering climate changes. The constants of Henry’s law are desired for assessing the processes related to…