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For: Jagiella N, Müller B, Müller M, Vignon-Clementel IE, Drasdo D. Inferring Growth Control Mechanisms in Growing Multi-cellular Spheroids of NSCLC Cells from Spatial-Temporal Image Data. PLoS Comput Biol 2016;12:e1004412. [PMID: 26866479 DOI: 10.1371/journal.pcbi.1004412] [Cited by in Crossref: 46] [Cited by in F6Publishing: 35] [Article Influence: 7.7] [Reference Citation Analysis]
Number Citing Articles
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2 Van Liedekerke P, Buttenschön A, Drasdo D. Off-Lattice Agent-Based Models for Cell and Tumor Growth. Numerical Methods and Advanced Simulation in Biomechanics and Biological Processes. Elsevier; 2018. pp. 245-67. [DOI: 10.1016/b978-0-12-811718-7.00014-9] [Cited by in Crossref: 15] [Article Influence: 3.8] [Reference Citation Analysis]
3 Moraes GS, Wink MR, Klamt F, Silva AO, da Cruz Fernandes M. Simplified low-cost methodology to establish, histologically process and analyze three-dimensional cancer cell spheroid arrays. Eur J Cell Biol 2020;99:151095. [PMID: 32646644 DOI: 10.1016/j.ejcb.2020.151095] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
4 Reher D, Klink B, Deutsch A, Voss-Böhme A. Cell adhesion heterogeneity reinforces tumour cell dissemination: novel insights from a mathematical model. Biol Direct 2017;12:18. [PMID: 28800767 DOI: 10.1186/s13062-017-0188-z] [Cited by in Crossref: 24] [Cited by in F6Publishing: 18] [Article Influence: 4.8] [Reference Citation Analysis]
5 Murphy RJ, Browning AP, Gunasingh G, Haass NK, Simpson MJ. Designing and interpreting 4D tumour spheroid experiments. Commun Biol 2022;5. [DOI: 10.1038/s42003-022-03018-3] [Reference Citation Analysis]
6 Lejeune E, Linder C. Modeling mechanical inhomogeneities in small populations of proliferating monolayers and spheroids. Biomech Model Mechanobiol 2018;17:727-43. [PMID: 29197990 DOI: 10.1007/s10237-017-0989-0] [Cited by in Crossref: 8] [Cited by in F6Publishing: 4] [Article Influence: 1.6] [Reference Citation Analysis]
7 Hross S, Theis FJ, Sixt M, Hasenauer J. Mechanistic description of spatial processes using integrative modelling of noise-corrupted imaging data. J R Soc Interface 2018;15:20180600. [PMID: 30958238 DOI: 10.1098/rsif.2018.0600] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 0.7] [Reference Citation Analysis]
8 Tampakaki M, Oraiopoulou ME, Tzamali E, Tzedakis G, Makatounakis T, Zacharakis G, Papamatheakis J, Sakkalis V. PML Differentially Regulates Growth and Invasion in Brain Cancer. Int J Mol Sci 2021;22:6289. [PMID: 34208139 DOI: 10.3390/ijms22126289] [Reference Citation Analysis]
9 Montagud A, Ponce-de-leon M, Valencia A. Systems biology at the giga-scale: Large multiscale models of complex, heterogeneous multicellular systems. Current Opinion in Systems Biology 2021;28:100385. [DOI: 10.1016/j.coisb.2021.100385] [Cited by in Crossref: 6] [Cited by in F6Publishing: 2] [Article Influence: 6.0] [Reference Citation Analysis]
10 Harris LA, Beik S, Ozawa PMM, Jimenez L, Weaver AM. Modeling heterogeneous tumor growth dynamics and cell-cell interactions at single-cell and cell-population resolution. Curr Opin Syst Biol 2019;17:24-34. [PMID: 32642602 DOI: 10.1016/j.coisb.2019.09.005] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 2.3] [Reference Citation Analysis]
11 Buttenschön A, Edelstein-Keshet L. Bridging from single to collective cell migration: A review of models and links to experiments. PLoS Comput Biol 2020;16:e1008411. [PMID: 33301528 DOI: 10.1371/journal.pcbi.1008411] [Cited by in Crossref: 9] [Cited by in F6Publishing: 5] [Article Influence: 4.5] [Reference Citation Analysis]
12 Engblom S, Wilson DB, Baker RE. Scalable population-level modelling of biological cells incorporating mechanics and kinetics in continuous time. R Soc Open Sci 2018;5:180379. [PMID: 30225024 DOI: 10.1098/rsos.180379] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 1.8] [Reference Citation Analysis]
13 Oraiopoulou ME, Tzamali E, Tzedakis G, Liapis E, Zacharakis G, Vakis A, Papamatheakis J, Sakkalis V. Integrating in vitro experiments with in silico approaches for Glioblastoma invasion: the role of cell-to-cell adhesion heterogeneity. Sci Rep 2018;8:16200. [PMID: 30385804 DOI: 10.1038/s41598-018-34521-5] [Cited by in Crossref: 11] [Cited by in F6Publishing: 8] [Article Influence: 2.8] [Reference Citation Analysis]
14 Bull JA, Mech F, Quaiser T, Waters SL, Byrne HM. Mathematical modelling reveals cellular dynamics within tumour spheroids. PLoS Comput Biol 2020;16:e1007961. [PMID: 32810174 DOI: 10.1371/journal.pcbi.1007961] [Cited by in Crossref: 11] [Cited by in F6Publishing: 7] [Article Influence: 5.5] [Reference Citation Analysis]
15 Van Liedekerke P, Palm MM, Jagiella N, Drasdo D. Simulating tissue mechanics with agent-based models: concepts, perspectives and some novel results. Comp Part Mech 2015;2:401-44. [DOI: 10.1007/s40571-015-0082-3] [Cited by in Crossref: 120] [Cited by in F6Publishing: 32] [Article Influence: 17.1] [Reference Citation Analysis]
16 Jagiella N, Rickert D, Theis FJ, Hasenauer J. Parallelization and High-Performance Computing Enables Automated Statistical Inference of Multi-scale Models. Cell Syst 2017;4:194-206.e9. [PMID: 28089542 DOI: 10.1016/j.cels.2016.12.002] [Cited by in Crossref: 38] [Cited by in F6Publishing: 22] [Article Influence: 7.6] [Reference Citation Analysis]
17 Oraiopoulou ME, Tzamali E, Tzedakis G, Vakis A, Papamatheakis J, Sakkalis V. In Vitro/In Silico Study on the Role of Doubling Time Heterogeneity among Primary Glioblastoma Cell Lines. Biomed Res Int 2017;2017:8569328. [PMID: 29226151 DOI: 10.1155/2017/8569328] [Cited by in Crossref: 18] [Cited by in F6Publishing: 12] [Article Influence: 3.6] [Reference Citation Analysis]
18 Falco J, Agosti A, Vetrano IG, Bizzi A, Restelli F, Broggi M, Schiariti M, DiMeco F, Ferroli P, Ciarletta P, Acerbi F. In Silico Mathematical Modelling for Glioblastoma: A Critical Review and a Patient-Specific Case. J Clin Med 2021;10:2169. [PMID: 34067871 DOI: 10.3390/jcm10102169] [Reference Citation Analysis]
19 Schmitz A, Fischer SC, Mattheyer C, Pampaloni F, Stelzer EH. Multiscale image analysis reveals structural heterogeneity of the cell microenvironment in homotypic spheroids. Sci Rep 2017;7:43693. [PMID: 28255161 DOI: 10.1038/srep43693] [Cited by in Crossref: 24] [Cited by in F6Publishing: 20] [Article Influence: 4.8] [Reference Citation Analysis]
20 Karolak A, Poonja S, Rejniak KA. Morphophenotypic classification of tumor organoids as an indicator of drug exposure and penetration potential. PLoS Comput Biol 2019;15:e1007214. [PMID: 31310602 DOI: 10.1371/journal.pcbi.1007214] [Cited by in Crossref: 13] [Cited by in F6Publishing: 8] [Article Influence: 4.3] [Reference Citation Analysis]
21 Fischer SC; Center for Computational and Theoretical Biology, Department of Biology, Universität Würzburg, Würzburg, Germany. An Introduction to Image-Based Systems Biology of Multicellular Spheroids for Experimentalists and Theoreticians. In: Husi H, editor. Computational Biology. Codon Publications; 2019. pp. 1-18. [DOI: 10.15586/computationalbiology.2019.ch1] [Reference Citation Analysis]
22 Ganai N, Büscher T, Gompper G, Elgeti J. Mechanics of tissue competition: interfaces stabilize coexistence. New J Phys 2019;21:063017. [DOI: 10.1088/1367-2630/ab2475] [Cited by in Crossref: 8] [Cited by in F6Publishing: 3] [Article Influence: 2.7] [Reference Citation Analysis]
23 Hoehme S, Bertaux F, Weens W, Grasl-Kraupp B, Hengstler JG, Drasdo D. Model Prediction and Validation of an Order Mechanism Controlling the Spatiotemporal Phenotype of Early Hepatocellular Carcinoma. Bull Math Biol 2018;80:1134-71. [PMID: 29568983 DOI: 10.1007/s11538-017-0375-1] [Cited by in Crossref: 12] [Cited by in F6Publishing: 9] [Article Influence: 3.0] [Reference Citation Analysis]
24 Sego TJ, Glazier JA, Tovar A. Unification of aggregate growth models by emergence from cellular and intracellular mechanisms. R Soc Open Sci 2020;7:192148. [PMID: 32968501 DOI: 10.1098/rsos.192148] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
25 Cruz R, Guerrero P, Spill F, Alarcón T. Stochastic multi-scale models of competition within heterogeneous cellular populations: Simulation methods and mean-field analysis. J Theor Biol 2016;407:161-83. [PMID: 27457092 DOI: 10.1016/j.jtbi.2016.07.028] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 1.0] [Reference Citation Analysis]
26 Hoehme S, Friebel A, Hammad S, Drasdo D, Hengstler JG. Creation of Three-Dimensional Liver Tissue Models from Experimental Images for Systems Medicine. Methods Mol Biol 2017;1506:319-62. [PMID: 27830563 DOI: 10.1007/978-1-4939-6506-9_22] [Cited by in Crossref: 12] [Cited by in F6Publishing: 10] [Article Influence: 3.0] [Reference Citation Analysis]
27 Little JP, Pettet GJ, Hutmacher DW, Loessner D. SpheroidSim-Preliminary evaluation of a new computational tool to predict the influence of cell cycle time and phase fraction on spheroid growth. Biotechnol Prog 2018;34:1335-43. [PMID: 30009492 DOI: 10.1002/btpr.2692] [Reference Citation Analysis]
28 Leclerc M, Clément JAJ, Andrivon D, Hamelin FM. Assessing the effects of quantitative host resistance on the life-history traits of sporulating parasites with growing lesions. Proc Biol Sci 2019;286:20191244. [PMID: 31575367 DOI: 10.1098/rspb.2019.1244] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
29 Bernard D, Mondesert O, Gomes A, Duthen Y, Lobjois V, Cussat-Blanc S, Ducommun B. A checkpoint-oriented cell cycle simulation model. Cell Cycle 2019;18:795-808. [PMID: 30870080 DOI: 10.1080/15384101.2019.1591125] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
30 Macnamara CK. Biomechanical modelling of cancer: Agent‐based force‐based models of solid tumours within the context of the tumour microenvironment. Comp Sys Onco 2021;1. [DOI: 10.1002/cso2.1018] [Reference Citation Analysis]
31 Michel T, Fehrenbach J, Lobjois V, Laurent J, Gomes A, Colin T, Poignard C. Mathematical modeling of the proliferation gradient in multicellular tumor spheroids. J Theor Biol 2018;458:133-47. [PMID: 30145131 DOI: 10.1016/j.jtbi.2018.08.031] [Cited by in Crossref: 9] [Cited by in F6Publishing: 5] [Article Influence: 2.3] [Reference Citation Analysis]
32 Chaplain MAJ, Giverso C, Lorenzi T, Preziosi L. Derivation and Application of Effective Interface Conditions for Continuum Mechanical Models of Cell Invasion through Thin Membranes. SIAM J Appl Math 2019;79:2011-31. [DOI: 10.1137/19m124263x] [Cited by in Crossref: 6] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
33 Lejeune E, Linder C. Understanding the relationship between cell death and tissue shrinkage via a stochastic agent-based model. J Biomech 2018;73:9-17. [PMID: 29622482 DOI: 10.1016/j.jbiomech.2018.03.019] [Cited by in Crossref: 10] [Cited by in F6Publishing: 6] [Article Influence: 2.5] [Reference Citation Analysis]
34 Cortesi M, Liverani C, Mercatali L, Ibrahim T, Giordano E. An in-silico study of cancer cell survival and spatial distribution within a 3D microenvironment. Sci Rep 2020;10:12976. [PMID: 32737377 DOI: 10.1038/s41598-020-69862-7] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
35 Karolak A, Markov DA, McCawley LJ, Rejniak KA. Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues. J R Soc Interface 2018;15:20170703. [PMID: 29367239 DOI: 10.1098/rsif.2017.0703] [Cited by in Crossref: 52] [Cited by in F6Publishing: 40] [Article Influence: 17.3] [Reference Citation Analysis]
36 Szymańska Z, Cytowski M, Mitchell E, Macnamara CK, Chaplain MAJ. Computational Modelling of Cancer Development and Growth: Modelling at Multiple Scales and Multiscale Modelling. Bull Math Biol 2018;80:1366-403. [PMID: 28634857 DOI: 10.1007/s11538-017-0292-3] [Cited by in Crossref: 12] [Cited by in F6Publishing: 10] [Article Influence: 2.4] [Reference Citation Analysis]
37 Van Liedekerke P, Neitsch J, Johann T, Alessandri K, Nassoy P, Drasdo D. Quantitative cell-based model predicts mechanical stress response of growing tumor spheroids over various growth conditions and cell lines. PLoS Comput Biol 2019;15:e1006273. [PMID: 30849070 DOI: 10.1371/journal.pcbi.1006273] [Cited by in Crossref: 22] [Cited by in F6Publishing: 18] [Article Influence: 7.3] [Reference Citation Analysis]
38 de la Cruz R, Guerrero P, Calvo J, Alarcón T. Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth. J Comput Phys 2017;350:974-91. [PMID: 29200499 DOI: 10.1016/j.jcp.2017.09.019] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.0] [Reference Citation Analysis]
39 Lima EABF, Faghihi D, Philley R, Yang J, Virostko J, Phillips CM, Yankeelov TE. Bayesian calibration of a stochastic, multiscale agent-based model for predicting in vitro tumor growth. PLoS Comput Biol 2021;17:e1008845. [PMID: 34843457 DOI: 10.1371/journal.pcbi.1008845] [Reference Citation Analysis]
40 Gong C, Anders RA, Zhu Q, Taube JM, Green B, Cheng W, Bartelink IH, Vicini P, Wang B, Popel AS. Quantitative Characterization of CD8+ T Cell Clustering and Spatial Heterogeneity in Solid Tumors. Front Oncol 2018;8:649. [PMID: 30666298 DOI: 10.3389/fonc.2018.00649] [Cited by in Crossref: 14] [Cited by in F6Publishing: 16] [Article Influence: 4.7] [Reference Citation Analysis]
41 Leroy-Lerêtre M, Dimarco G, Cazales M, Boizeau ML, Ducommun B, Lobjois V, Degond P. Are Tumor Cell Lineages Solely Shaped by Mechanical Forces? Bull Math Biol 2017;79:2356-93. [PMID: 28852950 DOI: 10.1007/s11538-017-0333-y] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 0.4] [Reference Citation Analysis]