Download DLSM Fact Sheet
Maria Pires Pacheco
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| Faculty or Centre | Faculty of Science, Technology and Medicine | ||||
| Department | Department of Life Sciences and Medicine | ||||
| Postal Address |
Université du Luxembourg 6, avenue du Swing L-4367 Belvaux |
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| Campus Office | BioTech II Ketterthill, 4.11 | ||||
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| Telephone | (+352) 46 66 44 9969 | ||||
2022
Bruceine D Identified as a Drug Candidate against Breast Cancer by a Novel Drug Selection Pipeline and Cell Viability Assay.; ; ; ; ; ;
in Pharmaceuticals (Basel, Switzerland) (2022), 15(2),
Project-based learning course on metabolic network modelling in computational systems biology.; ; ; ; ; ; ; ; ; ; ;
in PLoS computational biology (2022), 18(1), 1009711
2021
Loss of Ambra1 promotes melanoma growth and invasion.; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;
in Nature communications (2021), 12(1), 2550
DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling.; ;
in iScience (2021), 24(11), 103331
A dynamic multi-tissue model to study human metabolism.; ; ;
in NPJ systems biology and applications (2021), 7(1), 5
Importance of the biomass formulation for cancer metabolic modeling and drug prediction.; ; ; ;
in iScience (2021), 24(10), 103110
2020
Towards the routine use of in silico screenings for drug discovery using metabolic modelling; ;
in Biochemical Society Transactions (2020)
Testing informed SIR based epidemiological model for COVID-19 in Luxembourg;
E-print/Working paper (2020)
2019
Integrated In Vitro and In Silico Modeling Delineates the Molecular Effects of a Synbiotic Regimen on Colorectal-Cancer-Derived Cells; ; ; ; ; ; ; ; ; ; ; ; ; ; ;
in Cell Reports (2019), 27
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 (2019)
Towards the network-based prediction of repurposed drugs using patient-specific metabolic models.; ;
in EBioMedicine (2019)
Identifying and targeting cancer-specific metabolism with network-based drug target prediction; ; ; ; ; ;
in EBioMedicine (2019), 43(May 2019), 98-106
The Power of LC-MS Based Multiomics: Exploring Adipogenic Differentiation of Human Mesenchymal Stem/Stromal Cells; ; ; ; ; ; ;
in Molecules (2019)
2018
The FASTCORE Family: For the Fast Reconstruction of Compact Context-Specific Metabolic Networks Models;
in Fondi, Marco (Ed.) Metabolic Network Reconstruction and Modeling (2018)
The FASTCORE Family: For the Fast Reconstruction of Compact Context-Specific Metabolic Networks Models.;
in Methods in Molecular Biology (2018), (1716), 101-110
2016
Benchmarking procedures for high-throughput context specific reconstruction algorithms; ;
in Frontiers in Physiology (2016)
2015
The neural stem cell fate determinant TRIM32 regulates complex behavioral traits; ; ; ; ; ; ;
in Frontiers in Cellular Neuroscience (2015)
Integrated metabolic modelling reveals cell-type specific epigenetic control points of the macrophage metabolic network; ; ; ; ; ; ; ;
in BMC Genomics (2015), 16(809),
Towards improved genome-scale metabolic network reconstructions: unification, transcript specificity and beyond.; ;
in Briefings in bioinformatics (2015)
2014
Fast reconstruction of compact context-specific metabolic network models; ;
in PLoS Computational Biology (2014), 10(1), 1003424
2013
Fast reconstruction of compact context-specific metabolic network models; ;
E-print/Working paper (2013)
Fastcore: An algorithm for fast reconstruction of context-specific metabolic network models; ;
in Proc. 8th BeNeLux Bioinformatics Conference (2013)
