Applied Mathematics

Applied Mathematics

ISSN Print: 2152-7385
ISSN Online: 2152-7393
www.scirp.org/journal/am
E-mail: am@scirp.org
"A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains"
written by Jan Poleszczuk, Heiko Enderling,
published by Applied Mathematics, Vol.5 No.1, 2014
has been cited by the following article(s):
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[1] A Review of Mathematical and Computational Methods in Cancer Dynamics
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[2] Developing a Scalable Cellular Automaton Model of 3D Tumor Growth
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[3] Modelling Direct and Indirect Effects of Radiation: Experimental, Clinical and Environmental Implications
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[4] Pattern formation and travelling waves in a multiphase moving boundary model of tumour growth
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[5] Study of Tumour Induced Vessel Displacement in the Tumour Progression Rate with Advanced Bioinspired Computational Tools
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[6] Machine Learning Techniques and Stochastic Modeling in Mathematical Oncology
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[7] Cellular-automaton simulation of tumor growth dynamics: from computational implementation to case analysis
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[8] Versatilidad y eficiencia de los autómatas celulares para la simulación y análisis de sistemas complejos en Ingeniería
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[9] Hybrid Simulations: New Directions in Combining Machine Learning and Discrete Models
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[10] Physics-Infused Hybrid Machine Learning Models and Their Applications
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[11] Impact of mechanically-regulated auxin transport dynamics on plant morphogenesis
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[12] Selection-driven tumor evolution with public goods leads to patterns of clonal expansion consistent with neutral growth
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[13] Fractional Mathematical Oncology: On the potential of non-integer order calculus applied to interdisciplinary models
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[14] Growth of tumours with stem cells: The effect of crowding and ageing of cells
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[15] Comparing Implementations of Cellular Automata as Images: A Novel Approach to Verification by Combining Image Processing and Machine Learning
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[16] Design and evaluation of update schemes to optimize asynchronous Cellular Automata with random or cyclic orders
2021 IEEE/ACM 25th …, 2021
[17] Selection-driven tumor evolution involving non-cell growth promotion leads to patterns of clonal expansion consistent with neutrality interpretation
2020
[18] Dynamic Load Balancing in Parallel Execution of Cellular Automata
2020
[19] Selection driven tumor evolution involving non-cell autonomous environmental engineering leads to patterns of clonal expansion consistent with neutral evolution
2020
[20] Life-Like Network Automata descriptor based on binary patterns for network classification
2020
[21] Biomedical Engineering Group, Universidad de Sevilla, Seville, Spain
2020
[22] Development of a Coupled Simulation Toolkit for Computational Radiation Biology Based on Geant4 and CompuCell3D
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[23] Mathematical Modelling Reveals Selective Dynamics Invisible to Imaging
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[24] Performance and soundness of simulation: a case study based on a cellular automaton for in-body spread of HIV
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[25] Selection driven tumor evolution involving non-cell autonomous environmental engineering leads to patterns of clonal expansion consistent with neutral …
2020
[26] Uncertainty quantification on a spatial Markov-chain model for the progression of skin cancer
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[27] PI-LSTM: Physics-infused long short-term memory network
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[28] Dynamic load balancing strategy for parallel tumor growth simulations
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[29] A Review of Cell-Based Computational Modeling in Cancer Biology
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[30] Hybrid Machine Learning Approach for Predictive Modeling of Complex Systems
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[31] Methods and practice of detecting selection in human cancers
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[32] An In Silico Cell Signaling-Based Approach for Exploring the Activities Involved in Pre-Metastasis and Metastasis
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[33] Mathematical Modelling and Computer Simulations in Undergraduate Biology Education
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[34] Autômato Celular 3D Aplicado à Simulação Computacional da Evolução de Volumes Tumorais
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[35] Photodynamic therapy: Toward a systemic computational model
Journal of Photochemistry and Photobiology B: Biology, 2018
[36] Parallel Cellular Automaton Tumor Growth Model
Practical Applications of Computational Biology and Bioinformatics, 12th International Conference, 2018
[37] Hybrid multiscale modeling and prediction of cancer cell behavior
PLOS ONE, 2017
[38] Cell adhesion heterogeneity reinforces tumour cell dissemination: novel insights from a mathematical model
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[39] Teaching concurrent and parallel programming by patterns: An interactive ICT approach
Journal of Parallel and Distributed Computing, 2017
[40] Variance-Reduced Simulation of Multiscale Tumor Growth Modeling
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[41] Cellular automaton model of radiation damage to the tumor
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[42] Sampling from single-cell observations to predict tumor cell growth in-vitro and in-vivo
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[43] Speeding Up Tumor Growth Simulations Using Parallel Programming and Cellular Automata
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[44] Mechanically-Driven Pattern Formation in Cell Cultures
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[45] MultiCellDS: a community-developed standard for curating microenvironment-dependent multicellular data
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[46] Variance reduction for multiscale tumor growth modeling
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[47] Evolution and phenotypic selection of cancer stem cells
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[48] Cancer stem cell plasticity as tumor growth promoter and catalyst of population collapse
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[49] From concept to clinic: mathematically informed immunotherapy
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[50] Extremely high genetic diversity in a single tumor points to prevalence of non-Darwinian cell evolution
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[51] Agent-based modeling of cancer stem cell driven solid tumor growth
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[52] Vectorization techniques for efficient agent-based model simulations of tumor growth
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[53] Physics-Infused Learning: A DNN and GAN Approach
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