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BMC Bioinformatics|August 2, 2018
Emerging ensembles of kinetic parameters to characterize observed metabolic phenotypesRiccardo Colombo, Chiara Damiani, David Gilbert, et al.Bioinformatics (Oxford, England)|September 9, 2017
popFBA: tackling intratumour heterogeneity with Flux Balance AnalysisChiara Damiani, Marzia Di Filippo, Dario Pescini, et al.Plos Computational Biology|December 18, 2025
Mechanistically informed machine learning links non-canonical TCA cycle activity to Warburg metabolism and hallmarks of malignancyLihao Lin, Francesco Lapi, Bruno Giovanni Galuzzi, et al.Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|January 11, 2011
Dynamical properties of a boolean model of gene regulatory network with memoryAlex Graudenzi, Roberto Serra, Marco Villani, et al.Frontiers in Oncology|May 15, 2023
Tumor heterogeneity: preclinical models, emerging technologies, and future applicationsMarco Proietto, Martina Crippa, Chiara Damiani, et al.Bioinformatics (Oxford, England)|December 21, 2025
COBRAxy: Constraint-based metabolic modelling in GalaxyFrancesco Lapi, Luca Milazzo, Lihao Lin, et al.Journal of Chemical Information and Modeling|September 20, 2022
Machine Learning for Efficient Prediction of Protein Redox Potential: The Flavoproteins CaseBruno Giovanni Galuzzi, Antonio Mirarchi, Edoardo Luca Viganò, et al.Methods in Molecular Biology (Clifton, N.J.)|January 2, 2020
Single-cell Digital Twins for Cancer Preclinical InvestigationMarzia Di Filippo, Chiara Damiani, Marco Vanoni, et al.Computational Biology and Chemistry|April 18, 2016
Zooming-in on cancer metabolic rewiring with tissue specific constraint-based modelsMarzia Di Filippo, Riccardo Colombo, Chiara Damiani, et al.Current Genomics|July 5, 2021
On the Use of Topological Features of Metabolic Networks for the Classification of Cancer SamplesJeaneth Machicao, Francesco Craighero, Davide Maspero, et al.Pageof 4