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“Graduate (1991) PhD (Complutense U., Madrid, 1995). Associate professor (1997) and full professor (2002) in Applied Mathematics at the Mathematics Department of the University of Castilla-La Mancha. He has published more than 170 research papers with more than 11000 Google citations and has an H-index of 52. He is editor in chief of the journal “Physica D: “Nonlinear Phenomena” and serves in the editorial board of “npj Systems Biology and Applications”. He is the coordinator of the Applied Mathematics panel at the Spanish National Research Agency and has been a member of the Marie Curie evaluation committee and of many international project evaluation boards in oncology and/or applied mathematics in France, UK, Poland, Austria, Romania, Cyprus, Latvia, Spain, etc. His main field of research is the application of mathematical modeling to oncology and more specifically to brain tumors, metastasis, cellular immunotherapies, biomarkers, medical images, lymphomas, leukaemias, prostate cancer, etc. In this field he has led several projects funded by public institutions, private foundations such as the James S. Mc. Donnell Foundation and pharmaceutical companies such as NOVARTIS. More specifically he is interested in the development and validation of mechanistic mathematical models that shed light on oncological processes and may be used as platforms to personalize treatments and develop in-silico trials. Also he is interested in the development of mathematical model-based biomarkers of response to treatments.” |
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A three-dimensional computational analysis of magnetic resonance images characterizes the biological aggressiveness in malignant brain tumors
Journal of the Royal Society Interface 15, 20180503 (2018).
J. Pérez-Beteta, A. Martínez-González, V.M. Pérez-García -
Intratumoral heterogeneity in 18F-FDG PET/CT by textural analysis in breast cancer as predictive and prognostic subrogate.
Annals of Nuclear Medicine 32(6), 379-388 (2018).
D. Molina A.M. García Vicente, J. Pérez-Beteta, M. Amo-Salas, A. Martínez-González, M.J. Tello Galán, A. Soriano, V.M. Pérez-García -
Labile Hemoglobin as a Glycemic Biomarker for Patient-Specific Monitoring of Diabetes: Mathematical Modelling Approach
Journal of the Royal Society Interface, 15(142), 20180224 (2018)
O. León-Triana, G.F. Calvo, J. Belmonte-Beitia, M. Rosa Durán, J. Escribano-Serrano, A. Michan-Doña, V.M. Pérez-García -
Regulation of the oxidative balance with Coenzyme Q10 sensitizes human glioblastoma cells to radiation and temozolomide
Radiotherapy and Oncology 128(2) 236-244 (2018)
J. Frontiñán, R. Santiago, C. Nieva, G. Ferrín, A. Martínez, M.V. Gomez, M. Moreno, J. Ariza, E. Lozano, J. Arjona, A. Gil, M. De la Mata, M. Pesic, J.R. Peinado, J.M. Villalba, L.A. Pérez-Romasanta, V.M. Pérez-García, F.J. Alcaín, M. Durán-Prado -
Towards Uncertainty-Assisted Brain Tumor Segmentation and Survival Prediction
In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2017. Lecture Notes in Computer Science, vol 10670. Springer
A. Jungo, R. McKinley, R. Meier, U. Knecht, L. Vera, J. Pérez-Beteta, D. Molina, V.M. Pérez-García, R. Wiest, M. Reyes -
Tumor Surface Regularity at MR Imaging Predicts Survival and Response to Surgery in Patients with Glioblastoma
Radiology 288(1), 218-225 (2018)
J. Pérez-Beteta, D. Molina, A. Fernández, B. Luque, E. Arregui, M. Calvo, J. M. Borrás, A. Fernández-Romero, B. Luque, B. Meléndez, A.R. de Lope, R. Moreno, L. Iglesias, J.A. Barcia, J. Martino, C. Velasquez, B. Asenjo, M. Benavides, I. Herruzo, A. Revert, E. Arana, V. M. Pérez-García
- Establishing a non-invasive approach to accurately diagnose and assess brain tumors
Canadian Cancer Society (2024 - 2027) - Improving New Therapies in Oncology and Related Fields using mathematical models and biomedical data
Ministry of Science and Innovation (National Research Plan) (2023 - 2026) - Mathematical models for the digital transition in neuro-oncology: In-silico design of a clinical trial for glioblastoma.
Ministerio de Ciencia e Innovación (NextGenerationEU) (2023 - 2024) - Optimization of tisagenlecleucel treatments of lymphoma: An integrated human data-based approach using mathematical models
NOVARTIS (2023 - 2025) - Validation and transfer of oncological data and biomarkers based on mathematical models (AFTERbioMATH)
Ministry of Science and Innovation (Spain), Proof of Concept Program (2023 - 2024) - Early identification of relapse and treatment optimization in acute lymphoblastic leukaemias through mathematical modelling and discriminant analysis
Junta de Andalucía (2020 - 2023) - Improving cell therapies in neuroblastoma through mathematical modelling
NeN Association (2020 - 2023) - Mathematical models in Oncology
Ministerio de Ciencia e Innovación (Spain) (2020 - 2023)
“Graduate (1991) PhD (Complutense U., Madrid, 1995). Associate professor (1997) and full professor (2002) in Applied Mathematics at the Mathematics Department of the University of Castilla-La Mancha. He has published more than 170 research papers with more than 11000 Google citations and has an H-index of 52. He is editor in chief of the journal “Physica D: “Nonlinear Phenomena” and serves in the editorial board of “npj Systems Biology and Applications”. He is the coordinator of the Applied Mathematics panel at the Spanish National Research Agency and has been a member of the Marie Curie evaluation committee and of many international project evaluation boards in oncology and/or applied mathematics in France, UK, Poland, Austria, Romania, Cyprus, Latvia, Spain, etc. His main field of research is the application of mathematical modeling to oncology and more specifically to brain tumors, metastasis, cellular immunotherapies, biomarkers, medical images, lymphomas, leukaemias, prostate cancer, etc. In this field he has led several projects funded by public institutions, private foundations such as the James S. Mc. Donnell Foundation and pharmaceutical companies such as NOVARTIS. More specifically he is interested in the development and validation of mechanistic mathematical models that shed light on oncological processes and may be used as platforms to personalize treatments and develop in-silico trials. Also he is interested in the development of mathematical model-based biomarkers of response to treatments.” |
- A three-dimensional computational analysis of magnetic resonance images characterizes the biological aggressiveness in malignant brain tumors
Journal of the Royal Society Interface 15, 20180503 (2018).
J. Pérez-Beteta, A. Martínez-González, V.M. Pérez-García - Intratumoral heterogeneity in 18F-FDG PET/CT by textural analysis in breast cancer as predictive and prognostic subrogate.
Annals of Nuclear Medicine 32(6), 379-388 (2018).
D. Molina A.M. García Vicente, J. Pérez-Beteta, M. Amo-Salas, A. Martínez-González, M.J. Tello Galán, A. Soriano, V.M. Pérez-García - Labile Hemoglobin as a Glycemic Biomarker for Patient-Specific Monitoring of Diabetes: Mathematical Modelling Approach
Journal of the Royal Society Interface, 15(142), 20180224 (2018)
O. León-Triana, G.F. Calvo, J. Belmonte-Beitia, M. Rosa Durán, J. Escribano-Serrano, A. Michan-Doña, V.M. Pérez-García - Regulation of the oxidative balance with Coenzyme Q10 sensitizes human glioblastoma cells to radiation and temozolomide
Radiotherapy and Oncology 128(2) 236-244 (2018)
J. Frontiñán, R. Santiago, C. Nieva, G. Ferrín, A. Martínez, M.V. Gomez, M. Moreno, J. Ariza, E. Lozano, J. Arjona, A. Gil, M. De la Mata, M. Pesic, J.R. Peinado, J.M. Villalba, L.A. Pérez-Romasanta, V.M. Pérez-García, F.J. Alcaín, M. Durán-Prado - Towards Uncertainty-Assisted Brain Tumor Segmentation and Survival Prediction
In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2017. Lecture Notes in Computer Science, vol 10670. Springer
A. Jungo, R. McKinley, R. Meier, U. Knecht, L. Vera, J. Pérez-Beteta, D. Molina, V.M. Pérez-García, R. Wiest, M. Reyes - Tumor Surface Regularity at MR Imaging Predicts Survival and Response to Surgery in Patients with Glioblastoma
Radiology 288(1), 218-225 (2018)
J. Pérez-Beteta, D. Molina, A. Fernández, B. Luque, E. Arregui, M. Calvo, J. M. Borrás, A. Fernández-Romero, B. Luque, B. Meléndez, A.R. de Lope, R. Moreno, L. Iglesias, J.A. Barcia, J. Martino, C. Velasquez, B. Asenjo, M. Benavides, I. Herruzo, A. Revert, E. Arana, V. M. Pérez-García
- Establishing a non-invasive approach to accurately diagnose and assess brain tumors
Canadian Cancer Society (2024 - 2027) - Improving New Therapies in Oncology and Related Fields using mathematical models and biomedical data
Ministry of Science and Innovation (National Research Plan) (2023 - 2026) - Mathematical models for the digital transition in neuro-oncology: In-silico design of a clinical trial for glioblastoma.
Ministerio de Ciencia e Innovación (NextGenerationEU) (2023 - 2024) - Optimization of tisagenlecleucel treatments of lymphoma: An integrated human data-based approach using mathematical models
NOVARTIS (2023 - 2025) - Validation and transfer of oncological data and biomarkers based on mathematical models (AFTERbioMATH)
Ministry of Science and Innovation (Spain), Proof of Concept Program (2023 - 2024) - Early identification of relapse and treatment optimization in acute lymphoblastic leukaemias through mathematical modelling and discriminant analysis
Junta de Andalucía (2020 - 2023) - Improving cell therapies in neuroblastoma through mathematical modelling
NeN Association (2020 - 2023) - Mathematical models in Oncology
Ministerio de Ciencia e Innovación (Spain) (2020 - 2023)