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Integration of transcriptomic data and metabolic networks in cancer samples reveals highly significant prognostic power.

, , , , , , , , and . Journal of Biomedical Informatics, (2018)

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A stochastic model of autocatalytic reaction networks., , , , , , , and . Theory in Biosciences, 131 (2): 85-93 (2012)Preface., , and . Natural Computing, 13 (3): 285-286 (2014)Dynamical Properties of a Boolean Model of Gene Regulatory Network with Memory., , , , , and . Journal of Computational Biology, 18 (10): 1291-1303 (2011)The Influence of Nutrients Diffusion on a Metabolism-driven Model of a Multi-cellular System., , , , , , , , , and . Fundam. Informaticae, 171 (1-4): 279-295 (2020)The role of energy in a stochastic model of the emergence of autocatalytic sets., , , , , and . ECAL, page 226-233. MIT Press, (2011)CAPRI: efficient inference of cancer progression models from cross-sectional data., , , , , , , and . Bioinformatics, 31 (18): 3016-3026 (2015)Modeling Spatio-Temporal Dynamics of Metabolic Networks with Cellular Automata and Constraint-Based Methods., , and . ACRI, volume 11115 of Lecture Notes in Computer Science, page 16-29. Springer, (2018)On RAF Sets and Autocatalytic Cycles in Random Reaction Networks., , , , , , and . WIVACE, volume 445 of Communications in Computer and Information Science, page 113-126. Springer, (2014)PMCE: efficient inference of expressive models of cancer evolution with high prognostic power., , , , , and . Bioinform., 38 (3): 754-762 (2022)Genetic Regulatory Networks and Neural Networks., , and . WIRN, volume 193 of Frontiers in Artificial Intelligence and Applications, page 109-117. IOS Press, (2008)