  | KISHK, A., PIRES PACHECO, M. I., HEURTAUX, T., & SAUTER, T. (27 March 2024). Metabolic models predict fotemustine and the combination of eflornithine/rifamycin and adapalene/cannabidiol for the treatment of gliomas. Briefings in Bioinformatics, 25 (3). doi:10.1093/bib/bbae199  Peer Reviewed verified by ORBi |
 | KISHK, A. (2024). Towards Effective Prediction of Repurposable Drugs Through Metabolic Modeling: Evaluation Against Approved Drugs Using Preclinical and Clinical Data [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/61141 |
 | Bintener, T., PIRES PACHECO, M. I., PHILIPPIDOU, D., MARGUE, C., KISHK, A., Del Mistro, G., Di Leo, L., MOSCARDO GARCIA, M., HALDER, R., SINKKONEN, L., De Zio, D., KREIS, S., Kulms, D., & SAUTER, T. (26 July 2023). Metabolic modelling-based in silico drug target prediction identifies six novel repurposable drugs for melanoma. Cell Death and Disease, 14 (468). doi:10.1038/s41419-023-05955-1 Peer Reviewed verified by ORBi |
 | KISHK, A., PIRES PACHECO, M. I., HEURTAUX, T., SINKKONEN, L., PANG, J., Fritah, S., NICLOU, S., & SAUTER, T. (2022). Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases. Cells, 11 (16). doi:10.3390/cells11162486 Peer Reviewed verified by ORBi |
 | KISHK, A., PIRES PACHECO, M. I., & SAUTER, T. (2021). DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling. iScience, 24 (11), 103331. doi:10.1016/j.isci.2021.103331 Peer Reviewed verified by ORBi |
 | Di Leo, L., Pagliuca, C., KISHK, A., Rizza, S., Tsiavou, C., Pecorari, C., Dahl, C., PIRES PACHECO, M. I., Tholstrup, R., Brewer, J. R., Berico, P., Hernando, E., Cecconi, F., Ballotti, R., Bertolotto, C., Filomeni, G., Gjerstorff, M. F., SAUTER, T., Lovat, P., ... De Zio, D. (18 June 2024). AMBRA1 levels predict resistance to MAPK inhibitors in melanoma. Proceedings of the National Academy of Sciences of the United States of America, 121 (25), 2400566121. doi:10.1073/pnas.2400566121 Peer Reviewed verified by ORBi |
| KISHK, A., PIRES PACHECO, M. I., HEURTAUX, T., & SAUTER, T. (27 March 2024). Metabolic models predict fotemustine and the combination of eflornithine/rifamycin and adapalene/cannabidiol for the treatment of gliomas. Briefings in Bioinformatics, 25 (3). doi:10.1093/bib/bbae199 Peer Reviewed verified by ORBi |
| KISHK, A. (2024). Towards Effective Prediction of Repurposable Drugs Through Metabolic Modeling: Evaluation Against Approved Drugs Using Preclinical and Clinical Data [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/61141 |
| Bintener, T., PIRES PACHECO, M. I., PHILIPPIDOU, D., MARGUE, C., KISHK, A., Del Mistro, G., Di Leo, L., MOSCARDO GARCIA, M., HALDER, R., SINKKONEN, L., De Zio, D., KREIS, S., Kulms, D., & SAUTER, T. (26 July 2023). Metabolic modelling-based in silico drug target prediction identifies six novel repurposable drugs for melanoma. Cell Death and Disease, 14 (468). doi:10.1038/s41419-023-05955-1 Peer Reviewed verified by ORBi |
  | DIDIER, J., DE LANDTSHEER, S., PIRES PACHECO, M. I., KISHK, A., SCHNEIDER, J., Demuth, I., & SAUTER, T. (26 October 2022). Improving Machine Learning-based Prediction of Frailty in Elderly People with Digital Wearables : Data from the Berlin Aging Study II (BASE-II) [Poster presentation]. European Digital Medicine Conference Luxembourg 2022, Belval, Luxembourg. |
 | DIDIER, J., DE LANDTSHEER, S., PIRES PACHECO, M. I., KISHK, A., SCHNEIDER, J., Demuth, I., & SAUTER, T. (09 October 2022). Machine learning-based prediction of frailty in elderly people : Data from the Berlin Aging Study II (BASE-II) [Poster presentation]. 21st International Conference on Systems Biology, Berlin, Germany. |
 | SAUTER, T., Bintener, T., KISHK, A., PRESTA, L., Prohaska, T., Guignard, D., Zeng, N., Cipriani, C., Arshad, S., Pfau, T., MARTINS CONDE, P., & PIRES PACHECO, M. I. (2022). Project-based learning course on metabolic network modelling in computational systems biology. PLoS Computational Biology, 18 (1), 1009711. doi:10.1371/journal.pcbi.1009711 Peer Reviewed verified by ORBi |
 | Bintener, T., PIRES PACHECO, M. I., KISHK, A., DIDIER, J., & SAUTER, T. (2022). Drug Target Prediction Using Context-Specific Metabolic Models Reconstructed from rFASTCORMICS. In Methods in Molecular Biology (pp. 221-240). Clifton, N.J., United States: Springer. doi:10.1007/978-1-0716-2513-2_17 Peer reviewed |
 | Cipriani, C., PIRES PACHECO, M. I., KISHK, A., Wachich, M., ABANKWA, D., SCHAFFNER-RECKINGER, E., & SAUTER, T. (2022). Bruceine D Identified as a Drug Candidate against Breast Cancer by a Novel Drug Selection Pipeline and Cell Viability Assay. Pharmaceuticals (Basel, Switzerland), 15 (2). doi:10.3390/ph15020179 Peer reviewed |
| KISHK, A., PIRES PACHECO, M. I., HEURTAUX, T., SINKKONEN, L., PANG, J., Fritah, S., NICLOU, S., & SAUTER, T. (2022). Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases. Cells, 11 (16). doi:10.3390/cells11162486 Peer Reviewed verified by ORBi |
| KISHK, A., PIRES PACHECO, M. I., & SAUTER, T. (2021). DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling. iScience, 24 (11), 103331. doi:10.1016/j.isci.2021.103331 Peer Reviewed verified by ORBi |