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For: Alfonso JCL, Talkenberger K, Seifert M, Klink B, Hawkins-Daarud A, Swanson KR, Hatzikirou H, Deutsch A. The biology and mathematical modelling of glioma invasion: a review. J R Soc Interface 2017;14:20170490. [PMID: 29118112 DOI: 10.1098/rsif.2017.0490] [Cited by in Crossref: 86] [Cited by in F6Publishing: 66] [Article Influence: 21.5] [Reference Citation Analysis]
Number Citing Articles
1 Gallaher JA, Massey SC, Hawkins-Daarud A, Noticewala SS, Rockne RC, Johnston SK, Gonzalez-Cuyar L, Juliano J, Gil O, Swanson KR, Canoll P, Anderson ARA. From cells to tissue: How cell scale heterogeneity impacts glioblastoma growth and treatment response. PLoS Comput Biol 2020;16:e1007672. [PMID: 32101537 DOI: 10.1371/journal.pcbi.1007672] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 5.0] [Reference Citation Analysis]
2 Norton KA, Gong C, Jamalian S, Popel AS. Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment. Processes (Basel) 2019;7:37. [PMID: 30701168 DOI: 10.3390/pr7010037] [Cited by in Crossref: 46] [Cited by in F6Publishing: 38] [Article Influence: 15.3] [Reference Citation Analysis]
3 Morris B, Curtin L, Hawkins-Daarud A, Hubbard ME, Rahman R, Smith SJ, Auer D, Tran NL, Hu LS, Eschbacher JM, Smith KA, Stokes A, Swanson KR, Owen MR. Identifying the spatial and temporal dynamics of molecularly-distinct glioblastoma sub-populations. Math Biosci Eng 2020;17:4905-41. [PMID: 33120534 DOI: 10.3934/mbe.2020267] [Reference Citation Analysis]
4 Hormuth DA 2nd, Al Feghali KA, Elliott AM, Yankeelov TE, Chung C. Image-based personalization of computational models for predicting response of high-grade glioma to chemoradiation. Sci Rep 2021;11:8520. [PMID: 33875739 DOI: 10.1038/s41598-021-87887-4] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
5 Lorenzi T, Perthame B, Ruan X. Invasion fronts and adaptive dynamics in a model for the growth of cell populations with heterogeneous mobility. Eur J Appl Math. [DOI: 10.1017/s0956792521000218] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
6 Lipková J, Menze B, Wiestler B, Koumoutsakos P, Lowengrub JS. Modelling glioma progression, mass effect and intracranial pressure in patient anatomy. J R Soc Interface 2022;19:20210922. [PMID: 35317645 DOI: 10.1098/rsif.2021.0922] [Reference Citation Analysis]
7 Harkos C, Svensson SF, Emblem KE, Stylianopoulos T. Inducing Biomechanical Heterogeneity in Brain Tumor Modeling by MR Elastography: Effects on Tumor Growth, Vascular Density and Delivery of Therapeutics. Cancers (Basel) 2022;14:884. [PMID: 35205632 DOI: 10.3390/cancers14040884] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Stéphanou A, Ballet P, Powathil G, Volpert V. Hybrid data-based modelling in oncology: successes, challenges and hopes. Math Model Nat Phenom 2020;15:21. [DOI: 10.1051/mmnp/2019026] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
9 Katsushima K, Jallo G, Eberhart CG, Perera RJ. Long non-coding RNAs in brain tumors. NAR Cancer 2021;3:zcaa041. [PMID: 34316694 DOI: 10.1093/narcan/zcaa041] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
10 Ghaderi N, Jung J, Brüningk SC, Subramanian A, Nassour L, Peacock J. A Century of Fractionated Radiotherapy: How Mathematical Oncology Can Break the Rules. Int J Mol Sci 2022;23:1316. [PMID: 35163240 DOI: 10.3390/ijms23031316] [Reference Citation Analysis]
11 Pérez-Aliacar M, Doweidar MH, Doblaré M, Ayensa-Jiménez J. Predicting cell behaviour parameters from glioblastoma on a chip images. A deep learning approach. Comput Biol Med 2021;135:104547. [PMID: 34139437 DOI: 10.1016/j.compbiomed.2021.104547] [Reference Citation Analysis]
12 Bian A, Wang Y, Liu J, Wang X, Liu D, Jiang J, Ding L, Hui X. Circular RNA Complement Factor H (CFH) Promotes Glioma Progression by Sponging miR-149 and Regulating AKT1. Med Sci Monit 2018;24:5704-12. [PMID: 30111766 DOI: 10.12659/MSM.910180] [Cited by in Crossref: 17] [Cited by in F6Publishing: 16] [Article Influence: 4.3] [Reference Citation Analysis]
13 Sorribes IC, Handelman SK, Jain HV. Mitigating temozolomide resistance in glioblastoma via DNA damage-repair inhibition. J R Soc Interface 2020;17:20190722. [PMID: 31964274 DOI: 10.1098/rsif.2019.0722] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 3.5] [Reference Citation Analysis]
14 Kim Y, Kang H, Powathil G, Kim H, Trucu D, Lee W, Lawler S, Chaplain M. Role of extracellular matrix and microenvironment in regulation of tumor growth and LAR-mediated invasion in glioblastoma. PLoS One 2018;13:e0204865. [PMID: 30286133 DOI: 10.1371/journal.pone.0204865] [Cited by in Crossref: 19] [Cited by in F6Publishing: 19] [Article Influence: 4.8] [Reference Citation Analysis]
15 Jarrett AM, Kazerouni AS, Wu C, Virostko J, Sorace AG, DiCarlo JC, Hormuth DA 2nd, Ekrut DA, Patt D, Goodgame B, Avery S, Yankeelov TE. Quantitative magnetic resonance imaging and tumor forecasting of breast cancer patients in the community setting. Nat Protoc 2021;16:5309-38. [PMID: 34552262 DOI: 10.1038/s41596-021-00617-y] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
16 Modi U, Makwana P, Vasita R. Molecular insights of metastasis and cancer progression derived using 3D cancer spheroid co-culture in vitro platform. Crit Rev Oncol Hematol 2021;168:103511. [PMID: 34740822 DOI: 10.1016/j.critrevonc.2021.103511] [Reference Citation Analysis]
17 Angeli S, Emblem KE, Due-Tonnessen P, Stylianopoulos T. Towards patient-specific modeling of brain tumor growth and formation of secondary nodes guided by DTI-MRI. Neuroimage Clin 2018;20:664-73. [PMID: 30211003 DOI: 10.1016/j.nicl.2018.08.032] [Cited by in Crossref: 16] [Cited by in F6Publishing: 13] [Article Influence: 4.0] [Reference Citation Analysis]
18 Mahlbacher GE, Reihmer KC, Frieboes HB. Mathematical modeling of tumor-immune cell interactions. J Theor Biol 2019;469:47-60. [PMID: 30836073 DOI: 10.1016/j.jtbi.2019.03.002] [Cited by in Crossref: 36] [Cited by in F6Publishing: 17] [Article Influence: 12.0] [Reference Citation Analysis]
19 Mascheroni P, López Alfonso JC, Kalli M, Stylianopoulos T, Meyer-Hermann M, Hatzikirou H. On the Impact of Chemo-Mechanically Induced Phenotypic Transitions in Gliomas. Cancers (Basel) 2019;11:E716. [PMID: 31137643 DOI: 10.3390/cancers11050716] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 1.3] [Reference Citation Analysis]
20 Bosque JJ, Calvo GF, Pérez-García VM, Navarro MC. The interplay of blood flow and temperature in regional hyperthermia: a mathematical approach. R Soc Open Sci 2021;8:201234. [PMID: 33614070 DOI: 10.1098/rsos.201234] [Reference Citation Analysis]
21 Engwer C, Wenske M. Estimating the extent of glioblastoma invasion : Approximate stationalization of anisotropic advection-diffusion-reaction equations in the context of glioblastoma invasion. J Math Biol 2021;82:10. [PMID: 33496806 DOI: 10.1007/s00285-021-01563-9] [Reference Citation Analysis]
22 Fernández-romero A, Guillén-gonzález F, Suárez A. A Glioblastoma PDE-ODE model including chemotaxis and vasculature. ESAIM: M2AN 2022;56:407-31. [DOI: 10.1051/m2an/2022012] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
23 Sun R, Cuthbert H, Watts C. Fluorescence-Guided Surgery in the Surgical Treatment of Gliomas: Past, Present and Future. Cancers (Basel) 2021;13:3508. [PMID: 34298721 DOI: 10.3390/cancers13143508] [Reference Citation Analysis]
24 Reuter G, Lombard A, Suero Molina E, Scholtes F, Bianchi E. Hans Joachim Scherer: an under-recognized pioneer of glioma research in Belgium. Acta Neurol Belg 2021;121:867-72. [PMID: 33999386 DOI: 10.1007/s13760-021-01708-z] [Reference Citation Analysis]
25 Lipkova J, Angelikopoulos P, Wu S, Alberts E, Wiestler B, Diehl C, Preibisch C, Pyka T, Combs SE, Hadjidoukas P, Van Leemput K, Koumoutsakos P, Lowengrub J, Menze B. Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian Inference. IEEE Trans Med Imaging 2019;38:1875-84. [PMID: 30835219 DOI: 10.1109/TMI.2019.2902044] [Cited by in Crossref: 22] [Cited by in F6Publishing: 15] [Article Influence: 7.3] [Reference Citation Analysis]
26 López Alfonso JC, Parsai S, Joshi N, Godley A, Shah C, Koyfman SA, Caudell JJ, Fuller CD, Enderling H, Scott JG. Temporally feathered intensity-modulated radiation therapy: A planning technique to reduce normal tissue toxicity. Med Phys 2018;45:3466-74. [PMID: 29786861 DOI: 10.1002/mp.12988] [Cited by in Crossref: 11] [Cited by in F6Publishing: 10] [Article Influence: 2.8] [Reference Citation Analysis]
27 Gomez J, Holmes N, Hansen A, Adhikarla V, Gutova M, Rockne RC, Cho H; Department of Mathematics, University of California, Riverside, Riverside, CA 92521, USA, Division of Mathematical Oncology, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA, Department of Stem Cell Biology and Regenerative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA. . MBE 2022;19:2592-615. [DOI: 10.3934/mbe.2022119] [Reference Citation Analysis]
28 Heinrich MA, Mostafa AMRH, Morton JP, Hawinkels LJAC, Prakash J. Translating complexity and heterogeneity of pancreatic tumor: 3D in vitro to in vivo models. Adv Drug Deliv Rev 2021;174:265-93. [PMID: 33895214 DOI: 10.1016/j.addr.2021.04.018] [Cited by in Crossref: 12] [Cited by in F6Publishing: 10] [Article Influence: 12.0] [Reference Citation Analysis]
29 Finch A, Solomou G, Wykes V, Pohl U, Bardella C, Watts C. Advances in Research of Adult Gliomas. Int J Mol Sci 2021;22:E924. [PMID: 33477674 DOI: 10.3390/ijms22020924] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
30 Agosti A, Giverso C, Faggiano E, Stamm A, Ciarletta P. A personalized mathematical tool for neuro-oncology: A clinical case study. International Journal of Non-Linear Mechanics 2018;107:170-81. [DOI: 10.1016/j.ijnonlinmec.2018.06.004] [Cited by in Crossref: 10] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
31 Rynkeviciene R, Simiene J, Strainiene E, Stankevicius V, Usinskiene J, Miseikyte Kaubriene E, Meskinyte I, Cicenas J, Suziedelis K. Non-Coding RNAs in Glioma. Cancers (Basel). 2018;11:pii: E17. [PMID: 30583549 DOI: 10.3390/cancers11010017] [Cited by in Crossref: 50] [Cited by in F6Publishing: 50] [Article Influence: 12.5] [Reference Citation Analysis]
32 Bomzon Z, Wenger C, Proescholdt M, Mohan S. Tumor-Treating Fields at EMBC 2019: A Roadmap to Developing a Framework for TTFields Dosimetry and Treatment Planning. In: Makarov SN, Noetscher GM, Nummenmaa A, editors. Brain and Human Body Modeling 2020. Cham: Springer International Publishing; 2021. pp. 3-17. [DOI: 10.1007/978-3-030-45623-8_1] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
33 Conte M, Gerardo-giorda L, Groppi M. Glioma invasion and its interplay with nervous tissue and therapy: A multiscale model. Journal of Theoretical Biology 2020;486:110088. [DOI: 10.1016/j.jtbi.2019.110088] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
34 Pérez-beteta J, Belmonte-beitia J, Pérez-garcía VM, Hubert F. Tumor width on T1-weighted MRI images of glioblastoma as a prognostic biomarker: a mathematical model. Math Model Nat Phenom 2020;15:10. [DOI: 10.1051/mmnp/2019022] [Cited by in Crossref: 6] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
35 Hormuth DA 2nd, Jarrett AM, Davis T, Yankeelov TE. Towards an Image-Informed Mathematical Model of In Vivo Response to Fractionated Radiation Therapy. Cancers (Basel) 2021;13:1765. [PMID: 33917080 DOI: 10.3390/cancers13081765] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
36 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]
37 Yang B, Han ZY, Wang WJ, Ma YB, Chu SH. GNG5 is an unfavourable independent prognostic indicator of gliomas. J Cell Mol Med 2020;24:12873-8. [PMID: 33000557 DOI: 10.1111/jcmm.15923] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
38 Barreto N, Caballero M, Bonfanti AP, de Mato FCP, Munhoz J, da Rocha-E-Silva TAA, Sutti R, Vitorino-Araujo JL, Verinaud L, Rapôso C. Spider venom components decrease glioblastoma cell migration and invasion through RhoA-ROCK and Na+/K+-ATPase β2: potential molecular entities to treat invasive brain cancer. Cancer Cell Int 2020;20:576. [PMID: 33327966 DOI: 10.1186/s12935-020-01643-8] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
39 Mousavi SM, Derakhshan M, Baharloii F, Dashti F, Mirazimi SMA, Mahjoubin-Tehran M, Hosseindoost S, Goleij P, Rahimian N, Hamblin MR, Mirzaei H. Non-coding RNAs and glioblastoma: Insight into their roles in metastasis. Mol Ther Oncolytics 2022;24:262-87. [PMID: 35071748 DOI: 10.1016/j.omto.2021.12.015] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
40 Latini F, Fahlström M, Berntsson SG, Larsson EM, Smits A, Ryttlefors M. A novel radiological classification system for cerebral gliomas: The Brain-Grid. PLoS One 2019;14:e0211243. [PMID: 30677090 DOI: 10.1371/journal.pone.0211243] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 2.3] [Reference Citation Analysis]
41 Patsatzis DG. Algorithmic asymptotic analysis: Extending the arsenal of cancer immunology modeling. J Theor Biol 2022;534:110975. [PMID: 34883121 DOI: 10.1016/j.jtbi.2021.110975] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
42 Xia L, Jin P, Tian W, Liang S, Tan L, Li B. Up-regulation of MARVEL domain-containing protein 1 (MARVELD1) accelerated the malignant phenotype of glioma cancer cells via mediating JAK/STAT signaling pathway. Braz J Med Biol Res 2021;54:e10236. [PMID: 34008750 DOI: 10.1590/1414-431X2020e10236] [Reference Citation Analysis]
43 Jiang X, Chen D. LncRNA FAM181A-AS1 promotes gliomagenesis by sponging miR-129-5p and upregulating ZRANB2. Aging (Albany NY) 2020;12:20069-84. [PMID: 33080570 DOI: 10.18632/aging.103391] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
44 Kalinin V. Cell – extracellular matrix interaction in glioma growth. In silico model. Journal of Integrative Bioinformatics 2020;17. [DOI: 10.1515/jib-2020-0027] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
45 Zou Y, Huang L, Sun S, Yue F, Li Z, Ma Y, Ma H. Choline Kinase Alpha Promoted Glioma Development by Activating PI3K/AKT Signaling Pathway. Cancer Biother Radiopharm 2021. [PMID: 34788108 DOI: 10.1089/cbr.2021.0294] [Reference Citation Analysis]
46 Metzcar J, Wang Y, Heiland R, Macklin P. A Review of Cell-Based Computational Modeling in Cancer Biology. JCO Clin Cancer Inform. 2019;3:1-13. [PMID: 30715927 DOI: 10.1200/cci.18.00069] [Cited by in Crossref: 89] [Cited by in F6Publishing: 48] [Article Influence: 44.5] [Reference Citation Analysis]
47 Amend SR, Gatenby RA, Pienta KJ, Brown JS. Cancer Foraging Ecology: Diet Choice, Patch Use, and Habitat Selection of Cancer Cells. Curr Pathobiol Rep 2018;6:209-18. [DOI: 10.1007/s40139-018-0185-7] [Cited by in Crossref: 10] [Cited by in F6Publishing: 2] [Article Influence: 2.5] [Reference Citation Analysis]
48 Nava-Sedeño JM, Voß-Böhme A, Hatzikirou H, Deutsch A, Peruani F. Modelling collective cell motion: are on- and off-lattice models equivalent? Philos Trans R Soc Lond B Biol Sci 2020;375:20190378. [PMID: 32713300 DOI: 10.1098/rstb.2019.0378] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
49 Stanković T, Ranđelović T, Dragoj M, Stojković Burić S, Fernández L, Ochoa I, Pérez-García VM, Pešić M. In vitro biomimetic models for glioblastoma-a promising tool for drug response studies. Drug Resist Updat 2021;55:100753. [PMID: 33667959 DOI: 10.1016/j.drup.2021.100753] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
50 Lu MJ, Liu C, Lowengrub J, Li S. Complex Far-Field Geometries Determine the Stability of Solid Tumor Growth with Chemotaxis. Bull Math Biol 2020;82:39. [PMID: 32166456 DOI: 10.1007/s11538-020-00716-z] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
51 Conte M, Surulescu C. Mathematical modeling of glioma invasion: acid- and vasculature mediated go-or-grow dichotomy and the influence of tissue anisotropy. Applied Mathematics and Computation 2021;407:126305. [DOI: 10.1016/j.amc.2021.126305] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
52 Ma Z, Niu B, Phan TA, Stensjøen AL, Ene C, Woodiwiss T, Wang T, Maini PK, Holland EC, Tian JP. Stochastic growth pattern of untreated human glioblastomas predicts the survival time for patients. Sci Rep 2020;10:6642. [PMID: 32313150 DOI: 10.1038/s41598-020-63394-w] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
53 Vollmann-Zwerenz A, Leidgens V, Feliciello G, Klein CA, Hau P. Tumor Cell Invasion in Glioblastoma. Int J Mol Sci 2020;21:E1932. [PMID: 32178267 DOI: 10.3390/ijms21061932] [Cited by in Crossref: 25] [Cited by in F6Publishing: 29] [Article Influence: 12.5] [Reference Citation Analysis]
54 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]
55 Deutsch A, Friedl P, Preziosi L, Theraulaz G. Multi-scale analysis and modelling of collective migration in biological systems. Philos Trans R Soc Lond B Biol Sci 2020;375:20190377. [PMID: 32713301 DOI: 10.1098/rstb.2019.0377] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
56 Deng Y, Zhou L, Li N, Wang M, Yao L, Dong S, Zhang M, Yang P, Hao Q, Wu Y, Lyu L, Jin T, Dai Z, Kang H. Impact of four lncRNA polymorphisms (rs2151280, rs7763881, rs1136410, and rs3787016) on glioma risk and prognosis: A case-control study. Mol Carcinog 2019;58:2218-29. [PMID: 31489712 DOI: 10.1002/mc.23110] [Cited by in Crossref: 11] [Cited by in F6Publishing: 9] [Article Influence: 3.7] [Reference Citation Analysis]
57 Li R, Yang W. Gomisin J inhibits the glioma progression by inducing apoptosis and reducing HKII-regulated glycolysis. Biochem Biophys Res Commun 2020;529:15-22. [PMID: 32560813 DOI: 10.1016/j.bbrc.2020.05.109] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
58 Lu M, Hao W, Liu C, Lowengrub J, Li S. Nonlinear simulation of vascular tumor growth with chemotaxis and the control of necrosis. Journal of Computational Physics 2022;459:111153. [DOI: 10.1016/j.jcp.2022.111153] [Reference Citation Analysis]
59 Wang X, Wang H, Xu J, Hou X, Zhan H, Zhen Y. Double-targeting CDCA8 and E2F1 inhibits the growth and migration of malignant glioma. Cell Death Dis 2021;12:146. [PMID: 33542211 DOI: 10.1038/s41419-021-03405-4] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
60 Rauch P, Serra C, Regli L, Gruber A, Aichholzer M, Stefanits H, Kadri PADS, Tosic L, Gmeiner M, Türe U, Krayenbühl N. Cortical and Subcortical Anatomy of the Orbitofrontal Cortex: A White Matter Microfiberdissection Study and Case Series. Oper Neurosurg (Hagerstown) 2021:opab243. [PMID: 34245160 DOI: 10.1093/ons/opab243] [Reference Citation Analysis]
61 Chen YN, Hou SQ, Jiang R, Sun JL, Cheng CD, Qian ZR. EZH2 is a potential prognostic predictor of glioma. J Cell Mol Med 2021;25:925-36. [PMID: 33277782 DOI: 10.1111/jcmm.16149] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
62 Hu Y, Chu L, Liu J, Yu L, Song SB, Yang H, Han F. Knockdown of CREB3 activates endoplasmic reticulum stress and induces apoptosis in glioblastoma. Aging (Albany NY) 2019;11:8156-68. [PMID: 31612863 DOI: 10.18632/aging.102310] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
63 Latini F, Fahlström M, Beháňová A, Sintorn IM, Hodik M, Staxäng K, Ryttlefors M. The link between gliomas infiltration and white matter architecture investigated with electron microscopy and diffusion tensor imaging. Neuroimage Clin 2021;31:102735. [PMID: 34247117 DOI: 10.1016/j.nicl.2021.102735] [Reference Citation Analysis]
64 Hajishamsaei M, Pishevar A, Bavi O, Soltani M. A novel in silico platform for a fully automatic personalized brain tumor growth. Magn Reson Imaging 2020;68:121-6. [PMID: 31911200 DOI: 10.1016/j.mri.2019.12.012] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
65 Alsisi A, Eftimie R, Trucu D. Non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions. Math Biosci Eng 2021;18:5252-84. [PMID: 34517487 DOI: 10.3934/mbe.2021267] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
66 Ranjbar S, Singleton KW, Jackson PR, Rickertsen CR, Whitmire SA, Clark-Swanson KR, Mitchell JR, Swanson KR, Hu LS. A Deep Convolutional Neural Network for Annotation of Magnetic Resonance Imaging Sequence Type. J Digit Imaging 2020;33:439-46. [PMID: 31654174 DOI: 10.1007/s10278-019-00282-4] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
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