相似文献
1
Multiparameter computational modeling of tumor invasion.
Cancer Res. 2009 May 15;69(10):4493-501. doi: 10.1158/0008-5472.CAN-08-3834. Epub 2009 Apr 14.
2
Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.
Neuroimage. 2007;37 Suppl 1(Suppl 1):S120-34. doi: 10.1016/j.neuroimage.2007.05.043. Epub 2007 Jun 7.
3
Computational Trials: Unraveling Motility Phenotypes, Progression Patterns, and Treatment Options for Glioblastoma Multiforme.
PLoS One. 2016 Jan 12;11(1):e0146617. doi: 10.1371/journal.pone.0146617. eCollection 2016.
4
Prognostic significance of growth kinetics in newly diagnosed glioblastomas revealed by combining serial imaging with a novel biomathematical model.
Cancer Res. 2009 Dec 1;69(23):9133-40. doi: 10.1158/0008-5472.CAN-08-3863. Epub 2009 Nov 24.
5
Quantitative metrics of net proliferation and invasion link biological aggressiveness assessed by MRI with hypoxia assessed by FMISO-PET in newly diagnosed glioblastomas.
Cancer Res. 2009 May 15;69(10):4502-9. doi: 10.1158/0008-5472.CAN-08-3884. Epub 2009 Apr 14.
6
The impact of phenotypic switching on glioblastoma growth and invasion.
PLoS Comput Biol. 2012;8(6):e1002556. doi: 10.1371/journal.pcbi.1002556. Epub 2012 Jun 14.
7
Speed Switch in Glioblastoma Growth Rate due to Enhanced Hypoxia-Induced Migration.
Bull Math Biol. 2020 Mar 16;82(3):43. doi: 10.1007/s11538-020-00718-x.
8
Migration pathways of human glioblastoma cells xenografted into the immunosuppressed rat brain.
J Neurooncol. 2001 May;52(3):205-15. doi: 10.1023/a:1010620420241.
9
Image-driven modeling of the proliferation and necrosis of glioblastoma multiforme.
Theor Biol Med Model. 2017 May 2;14(1):10. doi: 10.1186/s12976-017-0056-7.
10
Computational modeling of tumor invasion from limited and diverse data in Glioblastoma.
Comput Med Imaging Graph. 2024 Oct;117:102436. doi: 10.1016/j.compmedimag.2024.102436. Epub 2024 Sep 23.
引用本文的文献
1
Mechanistic insight for T-cell exclusion by cancer-associated fibroblasts in human lung cancer.
Elife. 2025 Apr 10;13:RP101885. doi: 10.7554/eLife.101885.
2
Migration and proliferation drive the emergence of patterns in co-cultures of differentiating vascular progenitor cells.
Math Biosci Eng. 2024 Aug 1;21(8):6731-6757. doi: 10.3934/mbe.2024295.
3
Gradient-induced instability in tumour spheroids unveils the impact of microenvironmental nutrient changes.
Sci Rep. 2024 Sep 6;14(1):20837. doi: 10.1038/s41598-024-69570-6.
4
Morphological Stability for in silico Models of Avascular Tumors.
Bull Math Biol. 2024 May 17;86(7):75. doi: 10.1007/s11538-024-01297-x.
5
Hybrid Cellular Automata Modeling Reveals the Effects of Glucose Gradients on Tumour Spheroid Growth.
Cancers (Basel). 2023 Nov 30;15(23):5660. doi: 10.3390/cancers15235660.
6
From Chaos to Opportunity: Decoding Cancer Heterogeneity for Enhanced Treatment Strategies.
Biology (Basel). 2023 Aug 29;12(9):1183. doi: 10.3390/biology12091183.
7
A Mathematical Modelling Study of Chemotactic Dynamics in Cell Cultures: The Impact of Spatio-temporal Heterogeneity.
Bull Math Biol. 2023 Sep 8;85(10):98. doi: 10.1007/s11538-023-01194-9.
8
Data-driven spatio-temporal modelling of glioblastoma.
R Soc Open Sci. 2023 Mar 22;10(3):221444. doi: 10.1098/rsos.221444. eCollection 2023 Mar.
9
Evaluation of Lung Cancer Patient Response to First-Line Chemotherapy by Integration of Tumor Core Biopsy Metabolomics with Multiscale Modeling.
Ann Biomed Eng. 2023 Apr;51(4):820-832. doi: 10.1007/s10439-022-03096-8. Epub 2022 Oct 12.
10
Modeling of Tumor Growth with Input from Patient-Specific Metabolomic Data.
Ann Biomed Eng. 2022 Mar;50(3):314-329. doi: 10.1007/s10439-022-02904-5. Epub 2022 Jan 26.
本文引用的文献
1
Nonlinear simulations of solid tumor growth using a mixture model: invasion and branching.
J Math Biol. 2009 Apr;58(4-5):723-63. doi: 10.1007/s00285-008-0215-x. Epub 2008 Sep 12.
2
Predicting drug pharmacokinetics and effect in vascularized tumors using computer simulation.
J Math Biol. 2009 Apr;58(4-5):485-510. doi: 10.1007/s00285-008-0214-y. Epub 2008 Sep 10.
3
Three-dimensional multispecies nonlinear tumor growth--I Model and numerical method.
J Theor Biol. 2008 Aug 7;253(3):524-43. doi: 10.1016/j.jtbi.2008.03.027. Epub 2008 Mar 28.
4
Integrative mathematical oncology.
Nat Rev Cancer. 2008 Mar;8(3):227-34. doi: 10.1038/nrc2329.
5
Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.
Neuroimage. 2007;37 Suppl 1(Suppl 1):S120-34. doi: 10.1016/j.neuroimage.2007.05.043. Epub 2007 Jun 7.
6
Targeting the tumor microenvironment.
Front Biosci. 2007 May 1;12:3468-74. doi: 10.2741/2327.
7
Computer simulation of glioma growth and morphology.
Neuroimage. 2007;37 Suppl 1(Suppl 1):S59-70. doi: 10.1016/j.neuroimage.2007.03.008. Epub 2007 Mar 23.
8
Nonlinear simulation of the effect of microenvironment on tumor growth.
J Theor Biol. 2007 Apr 21;245(4):677-704. doi: 10.1016/j.jtbi.2006.12.004. Epub 2006 Dec 12.
9
Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment.
Cell. 2006 Dec 1;127(5):905-15. doi: 10.1016/j.cell.2006.09.042.
10
Mathematical modeling of cancer progression and response to chemotherapy.
Expert Rev Anticancer Ther. 2006 Oct;6(10):1361-76. doi: 10.1586/14737140.6.10.1361.
Zotero 插件