Profil

BINTENER Tamara Jean Rita

Main Referenced Co-authors
PACHECO, Maria  (6)
SAUTER, Thomas  (6)
HAAN, Serge  (2)
LETELLIER, Elisabeth  (2)
Baginska, joanna (1)
Main Referenced Keywords
Metabolic Modelling (4); cancer (3); Cancer (2); drug repositioning (2); Machine learning (2);
Main Referenced Unit & Research Centers
Luxembourg Centre for Systems Biomedicine (LCSB) (1)
Main Referenced Disciplines
Life sciences: Multidisciplinary, general & others (8)

Publications (total 8)

The most downloaded
222 downloads
PACHECO, M., BINTENER, T. J. R., TERNES, D., Kulms, D., HAAN, S., LETELLIER, E., & SAUTER, T. (May 2019). Identifying and targeting cancer-specific metabolism with network-based drug target prediction. EBioMedicine, 43 (May 2019), 98-106. doi:10.1016/j.ebiom.2019.04.046 https://hdl.handle.net/10993/39999

The most cited

54 citations (Scopus®)

GREENHALGH, K., RAMIRO GARCIA, J., Heinken, Ullmann, P., BINTENER, T. J. R., PACHECO, M., Baginska, J., SHAH, P., FRACHET BOUR, A., HALDER, R., FRITZ, J., SAUTER, T., Thiele, I., HAAN, S., LETELLIER, E., & WILMES, P. (30 April 2019). Integrated In Vitro and In Silico Modeling Delineates the Molecular Effects of a Synbiotic Regimen on Colorectal-Cancer-Derived Cells. Cell Reports, 27, 1621–1632. doi:10.1016/j.celrep.2019.04.001 https://hdl.handle.net/10993/39519

MOSCARDO GARCIA, M., PIRES PACHECO, M. I., BINTENER, T. J. R., PRESTA, L., & SAUTER, T. (2021). Importance of the biomass formulation for cancer metabolic modeling and drug prediction. iScience, 24 (10), 103110. doi:10.1016/j.isci.2021.103110
Peer Reviewed verified by ORBi

BINTENER, T. J. R. (2020). METABOLIC MODELLING BASED APPROACH TO IDENTIFY TAILORED METABOLIC DRUGS [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/48524

BINTENER, T. J. R., PIRES PACHECO, M. I., & SAUTER, T. (2020). Towards the routine use of in silico screenings for drug discovery using metabolic modelling. Biochemical Society Transactions. doi:10.1042/BST20190867
Peer Reviewed verified by ORBi

PACHECO, M., BINTENER, T. J. R., & SAUTER, T. (2019). Towards the Integration of Metabolic Network Modelling and Machine Learning for the Routine Analysis of High-Throughput Patient Data. In Automated Reasoning for Systems Biology and Medicine. Springer. doi:10.1007/978-3-030-17297-8_15

PACHECO, M., BINTENER, T. J. R., TERNES, D., Kulms, D., HAAN, S., LETELLIER, E., & SAUTER, T. (May 2019). Identifying and targeting cancer-specific metabolism with network-based drug target prediction. EBioMedicine, 43 (May 2019), 98-106. doi:10.1016/j.ebiom.2019.04.046
Peer Reviewed verified by ORBi

GREENHALGH, K., RAMIRO GARCIA, J., Heinken, Ullmann, P., BINTENER, T. J. R., PACHECO, M., Baginska, J., SHAH, P., FRACHET BOUR, A., HALDER, R., FRITZ, J., SAUTER, T., Thiele, I., HAAN, S., LETELLIER, E., & WILMES, P. (30 April 2019). Integrated In Vitro and In Silico Modeling Delineates the Molecular Effects of a Synbiotic Regimen on Colorectal-Cancer-Derived Cells. Cell Reports, 27, 1621–1632. doi:10.1016/j.celrep.2019.04.001
Peer Reviewed verified by ORBi

PACHECO, M., BINTENER, T. J. R., & SAUTER, T. (2019). Towards the network-based prediction of repurposed drugs using patient-specific metabolic models. EBioMedicine. doi:10.1016/j.ebiom.2019.04.017

BINTENER, T. J. R. (2016). Prediction of drug targets using metabolic modelling [Bachelor/master dissertation, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/39848

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