14 papers · ranked by Valyu relevance
Teresa T. Bucho, Renaud Tissier, Kevin Groot Lipman, Zuhir Bodalal + 4 more
RECIST is grounded on the assumption that target lesion selection is objective and representative of the change in total tumor burden during therapy. A computer simulation model was designed to challenge this assumption, focusing on a particular aspect of subjectivity: target lesion selection. Disagreement among…
Janine Egert, Clemens Kreutz
In systems biology, the analysis of complex nonlinear systems faces many methodological challenges. However, the performance evaluation of competing methods is limited by the small amount of publicly available data from biological experiments. Therefore, simulation studies with a realistic representation of the data…
Aarit Ahuja, Nadira Yusif Rodriguez, Alekh Karkada Ashok, Thomas Serre + 2 more
Visual simulation — i.e., using internal reconstructions of the world to experience potential future versions of events that are not currently happening — is among the most sophisticated capacities of the human mind. But is this ability in fact uniquely human? To answer this question, we tested monkeys on a series of…
Dan Spencer, Caitlin McKeown, David Tredwell, Benjamin Huckaby + 9 more
The development and use of virtual laboratories to augment traditional in-person skills training continues to grow. Virtual labs have been implemented in a number of diverse educational settings, which have many purported benefits including their adaptability, accessibility, and repeatability. However, few studies have…
Marco Augusto Sperandeo Liguori, André Ferreira Aparício, Thomaz A. A. Rocha e Silva
The integration of active learning strategies in health education is essential for improving student engagement and understanding, particularly in basic sciences like pharmacology and biochemistry. However, these disciplines are often perceived as abstract and disconnected from clinical practice. To develop and…
Randy Heiland, Daniel Bergman, Blair Lyons, Julie Cass + 4 more
Defining a multicellular model can be challenging. There may be hundreds of parameters that specify the attributes and behaviors of objects. Hopefully the model will be defined using some format specification, e.g., a markup language, that will provide easy model sharing (and a minimal step toward reproducibility).…
Riccardo Smeriglio, Roberta Bardini, Alessandro Savino, Stefano Di Carlo
In computational biology, in silico simulators are vital for exploring and understanding the behavior of complex biological systems. Hybrid multi-level simulators, such as PhysiCell and PhysiBoSS 2.0, integrate multiple layers of biological complexity, providing deeper insights into emergent patterns. However, one key…
James M. Osborne
In recent years, multi–cellular models, where cells are represented as individual interacting entities, are becoming ever popular. This has led to a proliferation of novel methods and simulation tools. The first aim of this paper is to review the numerical methods utilised by multi–cellular modelling tools and to…
Adam Streck, Tom Kaufmann, Roland F. Schwarz
Simulations of cancer evolution and cellular growth have proven highly useful to study, in detail, the various aspects of intra-tumour heterogeneity, including the effect of selection, mutation rates, and spatial constraints. However, most methods are computationally expensive lattice-embedded models which cannot…
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…
Jason Y. Cain, Jacob I. Evarts, Jessica S. Yu, Neda Bagheri
Emergent biological dynamics derive from the evolution of lower-level spatial and temporal processes. A long-standing challenge for scientists and engineers is identifying simple low-level rules that give rise to complex higher-level dynamics. High-resolution biological data acquisition enables this identification and…
Thaleia Ntiniakou, James Osborne, Jieling Zhao, Jules Dichamp + 30 more
The emergence of virtual human twins (VHT) in biomedical research has sparked interest in multiscale in silico modelling frameworks, particularly in their application bridging cellular to tissue levels. Among the diverse array of multiscale modelling tools, off-lattice center-based agent-based models (CBM) offer a…
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…
Daniel Bergman, Trachette L. Jackson
Agent-based models (ABMs) are an increasingly important tool for understanding the complexities presented by phenotypic and spatial heterogeneity in biological tissue. The resolution a modeler can achieve in these regards is unrivaled by other approaches. However, this comes at a steep computational cost limiting…