![]() ![]() | MOSCARDO GARCIA, M. (2024). MINIE: A MACHINE LEARNING NETWORK INFERENCE TOOL FOR TIME-SERIES MULTI-OMIC DATA [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/64220 |
![]() ![]() | 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 ![]() |
![]() ![]() | PIRES PACHECO, M. I., Ji, J., Prohaska, T., MOSCARDO GARCIA, M., & SAUTER, T. (2022). scFASTCORMICS: A Contextualization Algorithm to Reconstruct Metabolic Multi-Cell Population Models from Single-Cell RNAseq Data. Metabolites. ![]() |
![]() ![]() | MOSCARDO GARCIA, M., PIRES PACHECO, M. I., & SAUTER, T. (2022). Integration of external biomass reactions into existing metabolic models. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/52225. |
![]() ![]() | 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 ![]() |