
Publications
- Perlstein D, Shlagman O, Kogan Y, Halevi-Tobias K, Yakobson A, Lazarev I, et al. Personal response to immune checkpoint inhibitors of patients with advanced melanoma explained by a computational model of cellular immunity, tumor growth, and drug. PLoS One. 2019;14(12):e0226869. doi: 10.1371/journal.pone.0226869. PubMed PMID: 31877168.
- Tsur N, Kogan Y, Rehm M, Agur Z. Response of Patients with Melanoma to Immune Checkpoint Blockade – Insights Gleaned from Analysis of a New Mathematical Mechanistic Model. J Journal of Theoretical Biology 2019:110033. doi: 10.1016/j.jtbi.2019.110033. PubMed PMID: 31580835.
- Tsur N, Kogan Y, Avizov-Khodak E, Vaeth D, Vogler N, Utikal J, Lotem M, Agur Z. Predicting response to pembrolizumab in metastatic melanoma by a new personalization algorithm. J Journal of Translational Medicine 2019;17(1):338. doi: 10.1186/s12967-019-2081-2. PubMed PMID: 31590677.
- Kogan Y, Elishmereni M, Taub E, Agur Z. P-401 The tumor burden rise at radiological disease progression associates with poor overall survival in advanced colorectal cancer. Annals of Oncology (2019) 30(Supplement_4). doi: 10.1093/annonc/mdz183.006.
- Kogan Y, Shannon S, Taub E, Kleiman M, Elishmereni M, Agur Z. Predicting imminent disease progression in advanced colorectal cancer by a machine-learning algorithm. J Clin Oncol 37, 2019 (suppl 4; abstr 645)
- Kogan Y, Kleiman M, Shannon S, Elishmereni E, Taub E, Aptekar L, Brenner R. M, Berger R, Nechushtan H, Agur Z. A new algorithm predicting imminent disease progression in advanced NSCLC patients by machine-learning integration of five serum biomarkers. J Clin Oncol 36, 2018 (suppl; abstr e21190).
- Hochman G, Halevi-Tobias K, Kogan Y, Agur Z. Extracellular inhibitors can attenuate tumorigenic Wnt pathway activity in adenomatous polyposis coli mutants: Predictions of a validated mathematical model. J PLoS One 2017 Jul 14;12(7):e0179888.
- Agur Z, Halevi-Tobias K, Kogan Y, et al. Employing Dynamical Computational Models for Personalizing Cancer Immunotherapy. J Expert Opinion on Biological Therapy 2016 16(11) pp.1373-1385.
- Forys U, Bodnar M, Kogan Y.Asymptotic dynamics of some t-periodic one-dimensional model with application to prostate cancer immunotherapy. J Math Biol 2016 73(4) pp. 867-83 doi: 10.1007/s00285-016-0978-4.
- Kogan Y, Agur Z, Elishmereni M. A mathematical model for the immunotherapeutic control of the Th1/Th2 imbalance in melanoma. Discrete and Continuous Dynamics – Series B 2013, 18(4) pp. 1017-1030.doi:10.3934/dcdsb.2013.18.1017.
- Kogan Y, Halevi-Tobias K, Elishmereni M, Vuk Pavlović S, Agur Z. Reconsidering the Paradigm of Cancer Immunotherapy by Computationally Aided Real-Time Personalization Cancer Res. 2012 Mar 19. 72(9) pp.2218-2227, PMID: 22422938
- Kogan Y, Halevi-Tobias KE, Hochman G, Baczmanska AK, Leyns L, Agur, Z. A new validated mathematical model of the Wnt signaling pathway predicts effective combinational therapy by sFRP and Dkk Biochem J 2012. 444 pp. 115–125 PMID; 22356261
- Vainstein V, Kirnasovsky OU, Kogan Y, Agur Z. Strategies for cancer stem cell elimination: Insights from mathematical modeling. J Theor Biol. 2012 7(298) pp.32-41.
- Kronik N, Kogan Y, Schlegel PG, Wölfl M. Improving T-cell Immunotherapy for Melanoma Through a Mathematically Motivated Strategy: Efficacy in Numbers? Journal of Immunotherapy 2012 35(2) 110.1097/CJI.1090b1013e318236054c.
- Agur Z, Kirnasovsky OU, Vasserman G, Tencer-Hershkowicz L, Kogan Y, Harrison H, et al. Dickkopf1 regulates fate decision and drives breast cancer stem cells to differentiation: an experimentally supported mathematical model. PLoS one 2011 6(9) e24225
- Kronik N., Kogan Y., Elishmereni M., Halevi-Tobias K., Vuk Pavlović S., Agur Z. Predicting Effect of Prostate Cancer Immunotherapy by Personalized Mathematical Models PLoS one 2010 5(12) e15482
- Agur Z., Kogan Y., Levi L., Harrison H., Lamb R., Kirnasovsky O.U., Clarke R.B. Disruption of a Quorum Sensing Mechanism Triggers Tumorigenesis: a Simple Discrete Model Corroborated by Experiments in Mammary Cancer Stem Cells. Biol Direct 2010 5(1) pp.20-41.
- Kogan Y., Forys U., Shukron O., Kronik N., Agur Z. Cellular immunotherapy for high grade Gliomas: mathematical analysis deriving efficacious infusion rates based on patient requirements. SIAM J. Appl. Math. 2010 70(6) pp. 1953-1976.
- Kirnasovsky O.U., Kogan Y, Agur Z. Analysis of a mathematical model for the molecular mechanism of mammary stem cell fate decision. Mathematical Modelling of Natural Phenomena 2008 3(7) pp. 78-89.
- Kirnasovsky O.U., Kogan Y., Agur Z. Resilience in Stem Cell renewal: Development of the Agur – Daniel – Ginossar Model. Disc. Cont. Dyn. Systems 2008 10 pp.129- 148.
- Kogan Y., Ribba B., Dahan N., Marron K., Vainstein V., Agur Z. Intensifed Doxorubicin-Based Regimen Efficacy in Residual Non-Hodgkin’s Lymphoma Disease: Towards a Computationally Supported Treatment Improvement. Mathematical Modelling of Natural Phenomena 2007 2(3), pp. 47-68.
- Kronik N., Kogan Y., Vainstein V., Agur Z. Improving alloreactive CTL immunotherapy for malignant gliomas using a simulation model of their interactive dynamics. Cancer Immunol Immunother 2007 Mar;57(3):425-439 (2008). Epub 2007 Sep 7.
- Vainstein V., Ginosar Y., Shoham M., Ianovski A., Rabinovich A., Kogan Y., Selitser V., Agur Z. Improving cancer therapy by Doxorubicin and Granulocyte colony-stimulating factor: Insights from a Computerized Model of Human Granulopoiesis. Mathematical Modelling of Natural Phenomena 2006 1(2), pp.70-80.
- Forys U., Kheifetz Y., Kogan Y. Critical-point analysis for three-variable cancer angiogenesis modeling. Mathematical Biosciences and Engineering. 2005; 2 (3): 511-525.
- Kheifetz Y., Kogan Y. & Agur Z. Long-range predictability in models of cell populations subjected to phase-specific drugs: Growth-rate approximation using properties of positive compact operators. Mathematical Models & Methods in the Applied Sciences. 2006; 16 (7), 1-18.
- Kheifetz Y., Kogan Y., Agur Z. Matrix and compact operator description of resonance and antiresonance in cell populations subjected to phase specific drugs. Jour. Medical Informatics & Technologies. 2004; 8, MM-11 – MM-29.