| Integration of single-cell RNA-seq data into population models to characterize cancer metabolism C Damiani, D Maspero, M Di Filippo, R Colombo, D Pescini, A Graudenzi, ... PLoS computational biology 15 (2), e1006733, 2019 | 84 | 2019 |
| Zooming-in on cancer metabolic rewiring with tissue specific constraint-based models M Di Filippo, R Colombo, C Damiani, D Pescini, D Gaglio, M Vanoni, ... Computational biology and chemistry 62, 60-69, 2016 | 39 | 2016 |
| popFBA: tackling intratumour heterogeneity with Flux Balance Analysis C Damiani, M Di Filippo, D Pescini, D Maspero, R Colombo, G Mauri Bioinformatics 33 (14), i311-i318, 2017 | 31 | 2017 |
| INTEGRATE: Model-based multi-omics data integration to characterize multi-level metabolic regulation M Di Filippo, D Pescini, BG Galuzzi, M Bonanomi, D Gaglio, E Mangano, ... PLoS computational biology 18 (2), e1009337, 2022 | 30 | 2022 |
| Integration of transcriptomic data and metabolic networks in cancer samples reveals highly significant prognostic power A Graudenzi, D Maspero, M Di Filippo, M Gnugnoli, C Isella, G Mauri, ... Journal of biomedical informatics 87, 37-49, 2018 | 28 | 2018 |
| Single-cell digital twins for cancer preclinical investigation MD Filippo, C Damiani, M Vanoni, D Maspero, G Mauri, L Alberghina, ... Metabolic Flux Analysis in Eukaryotic Cells: Methods and Protocols, 331-343, 2020 | 23 | 2020 |
| GPRuler: Metabolic gene-protein-reaction rules automatic reconstruction M Di Filippo, C Damiani, D Pescini PLoS computational biology 17 (11), e1009550, 2021 | 19 | 2021 |
| MaREA4Galaxy: Metabolic reaction enrichment analysis and visualization of RNA-seq data within Galaxy C Damiani, L Rovida, D Maspero, I Sala, L Rosato, M Di Filippo, D Pescini, ... Computational and structural biotechnology journal 18, 993-999, 2020 | 9 | 2020 |
| Linking alterations in metabolic fluxes with shifts in metabolite levels by means of kinetic modeling C Damiani, R Colombo, M Di Filippo, D Pescini, G Mauri Advances in Artificial Life, Evolutionary Computation, and Systems Chemistry …, 2017 | 6 | 2017 |
| Constraint-based modeling and simulation of cell populations M Di Filippo, C Damiani, R Colombo, D Pescini, G Mauri Advances in Artificial Life, Evolutionary Computation, and Systems Chemistry …, 2017 | 6 | 2017 |
| Integration of single-cell RNA-seq data into metabolic models to characterize tumour cell populations C Damiani, D Maspero, M Di Filippo, R Colombo, D Pescini, A Graudenzi, ... bioRxiv, 256644, 2018 | 3 | 2018 |
| The influence of nutrients diffusion on a metabolism-driven model of a multi-cellular system D Maspero, C Damiani, M Antoniotti, A Graudenzi, M Di Filippo, M Vanoni, ... Fundamenta Informaticae 171 (1-4), 279-295, 2020 | 2 | 2020 |
| Genome-scale metabolic reconstruction of the stress-tolerant hybrid yeast Zygosaccharomyces parabailii MD Filippo, RA Ortiz-Merino, C Damiani, G Frascotti, D Porro, KH Wolfe, ... bioRxiv, 373621, 2018 | 2 | 2018 |
| A Mobile App Leveraging Citizenship Engagement to Perform Anonymized Longitudinal Studies in the Context of COVID-19 Adverse Drug Reaction Monitoring: Development and Usability … M Di Filippo, A Avellone, M Belingheri, ME Paladino, MA Riva, A Zambon, ... JMIR Human Factors 9 (4), e38701, 2022 | 1 | 2022 |
| Integration of single-cell rna-sequencing data into flux balance cellular automata D Maspero, M Di Filippo, F Angaroni, D Pescini, G Mauri, M Vanoni, ... Computational Intelligence Methods for Bioinformatics and Biostatistics …, 2020 | 1 | 2020 |
| MaREA: Metabolic feature extraction, enrichment and visualization of RNAseq data A Graudenzi, D Maspero, C Isella, MD Filippo, G Mauri, E Medico, ... bioRxiv, 248724, 2018 | 1 | 2018 |
| NEW CONSTRAINT-BASED APPROACHES TO TACKLE THE MULTIPLE SIDES OF CELL METABOLIC PLASTICITY AND HETEROGENEITY M Di Filippo Università degli Studi di Milano-Bicocca, 2019 | | 2019 |
| Metabolic enrichment through functional gene rules D Maspero, C Isella, M Di Filippo, A Graudenzi, SE Bellomo, M Antoniotti, ... arXiv preprint arXiv:1710.06017, 2017 | | 2017 |
| Applying data mining tools to infer species community structures from omics data G Agostinetto, M Di Filippo, A Sandionigi, D Pescini, M Casiraghi | | |
