25 papers · ranked by Valyu relevance
Andreas Tolk, Saikou Y. Diallo, José J. Padilla, Ross Gore
Epistemology is the branch of philosophy that deals with gaining knowledge. It is closely related to ontology. The branch that deals with questions like "What is real?" and "What do we know?" as it provides these components. When using modeling and simulation, we usually imply that we are doing so to either apply…
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…
Tiago Azevedo, Rosaldo J. F. Rossetti, Jorge G. Barbosa
—Nowadays, universities and companies have a huge need for simulation and modelling methodologies. In the particular case of traffic and transportation, making physical modifications to the real traffic networks could be highly expensive, dependent on political decisions and could be highly disruptive to the…
Alexander L.R. Lubbock, Carlos F. Lopez
Computational modeling has become an established technique to encode mathematical representations of cellular processes and gain mechanistic insights that drive testable predictions. These models are often constructed using graphical user interfaces or domain-specific languages, with SBML used for interchange. Models…
Adelinde M. Uhrmacher, Peter I. Frazier, Reiner Hähnle, Franziska Klügl + 8 more
'Franziska Klügl' 'Fabian Lorig' 'Bertram Ludäscher' 'Laura Nenzi' 'Cristina Ruiz-Martín' 'Bernhard Rumpe⋆' 'Claudia Szabo' 'Gabriel Wainer' 'Pia Wilsdorf'] Simulation has become, in many application areas, a sine-qua-non. Most recently, COVID-19 has underlined the importance of simulation studies and limitations in…
Florian Härtig
With the rise of computers, simulation models have emerged beside the more traditional statistical and mathematical models as a third pillar for ecological analysis. Broadly speaking, a simulation model is an algorithm, typically implemented as a computer program, which propagates the states of a system forward. Unlike…
Muffy Calder, Claire Craig, Dave Culley, Richard de Cani + 15 more
'Christl A. Donnelly' 'Rowan Douglas' 'Bruce Edmonds' 'Jonathon Gascoigne' 'Nigel Gilbert' 'Caroline Hargrove' 'Derwen Hinds' 'David C. Lane' 'Dervilla Mitchell' 'Giles Pavey' 'David Robertson' 'Bridget Rosewell' 'Spencer Sherwin' 'Mark Walport' 'Alan Wilson'] In order to deal with an increasingly complex world, we…
Erik Butterworth, Bartholomew E. Jardine, Gary M. Raymond, Maxwell L. Neal + 1 more
JSim is a simulation system for developing models, designing experiments, and evaluating hypotheses on physiological and pharmacological systems through the testing of model solutions against data. It is designed for interactive, iterative manipulation of the model code, handling of multiple data sets and parameter…
N. Furian, M. O’Sullivan, C. Walker, S. Vössner + 1 more
Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for…
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…
Alberto Fernández-Isabel, Rubén Fuentes-Fernández, Antonio Puliafito, Symeon Papavassiliou + 1 more
'Symeon Papavassiliou' 'Dario Bruneo'] Intelligent Transportation Systems (ITSs) integrate information, sensor, control, and communication technologies to provide transport related services. Their users range from everyday commuters to policy makers and urban planners. Given the complexity of these systems and their…
Seyed Mahdi Javadi, Seyed Jafar Sadjadi, Ahmad Makui
In manufacturing systems, simulation modeling plays an important role in creating some changes instead of working on real systems. Manipulation in a real system is more costly than manipulation in a simulated model. In this research, we tried to use a simulation approach to recognize and minimize bottlenecks of a…
Florian Cogoni, David Bernard, Roxana Kazhen, Salvatore Valitutti + 2 more
Agent-based models are commonly used in biology to study tissue-scale phenomena by reproducing the individual behavior of the cells. They offer the possibility to study cellular biology at the individual cell scale to explore the basic behavior of cells which are responsible of the emergence of more complex phenomena…
Olaf Wolkenhauer
Next generation sequencing technologies are bringing about a renaissance of mining approaches. A comprehensive picture of the genetic landscape of an individual patient will be useful, for example, to identify groups of patients that do or do not respond to certain therapies. The high expectations may however not be…
Feng Zhu, Yiping Yao, Huilong Chen, Feng Yao
Model reuse is a key issue to be resolved in parallel and distributed simulation at present. However, component models built by different domain experts usually have diversiform interfaces, couple tightly, and bind with simulation platforms closely. As a result, they are difficult to be reused across different…
Authors not listed
Digital twins are virtual companions for the design, scale-up, and control of chemical processes. Equipping digital twins with mechanistic models of their mirrored unit operation expands their range of applicability compared to pure data-driven models. As constructing mechanistic models requires time, effort, and…
Cornelius Steinbrink, Sebastian Lehnhoff, Sebastian Rohjans, Thomas Strasser + 21 more
'Thomas Strasser' 'E. Widl' 'C. Moyo' 'Georg Lauss' 'Felix Lehfuß' 'Mario Faschang' 'Peter Pálenský' 'A. van der Meer' 'Kai Heussen' 'Oliver Gehrke' 'Efren Guillo‐Sansano' 'Mazheruddin H. Syed' 'Abdullah Emhemed' 'Ron Brandl' 'Van Hoa Nguyen' 'A. Khavari' 'Quoc Tuan Tran' 'Panos Kotsampopoulos' 'Nikos Hatziargyriou'…
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…
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…
Niloofar Shahidi, Michael Pan, Soroush Safaei, Kenneth Tran + 2 more
Simulating complex biological and physiological systems and predicting their behaviours under different conditions remains challenging. Breaking systems into smaller and more manageable modules can address this challenge, assisting both model development and simulation. Nevertheless, existing computational models in…
Jessica S. Yu, Blair Lyons, Susanne Rafelski, Julie A. Theriot + 2 more
Iterating between data-driven research and generative computational models is a powerful approach for emulating biological systems, testing hypotheses, and gaining a deeper understanding of these systems. We developed a hybrid agent-based model (ABM) that integrates a Cellular Potts Model (CPM) designed to investigate…
Alan Aspuru-Guzik, Roland Lindh, Markus Reiher
To date, the program for the development of methods and models for atomistic and continuum simulation directed toward chemicals and materials has reached an incredible degree of sophistication and maturity. Currently, one can witness an increasingly rapid emergence of advances in computing, artificial intelligence, and…
Peter Sagmeister, Lukas Melnizky, Jason Williams, C. Oliver Kappe
In modern pharmaceutical research, the demand for expeditious development of synthetic routes to active pharmaceutical ingredients (APIs) has led to a paradigm shift towards data-rich process development. Conventional methodologies en-compass prolonged timelines for reaction and analytical model developments. Both…
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…
Zhenghao Wu, Tianhang Zhou
In the realm of multiscale molecular simulations, structure-based coarse graining is a prominent approach for creating efficient coarse-grained (CG) representations of soft matter systems such as polymers. This involves optimizing CG interactions by matching static correlation functions of corresponding degrees of…