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A metabolic core model elucidates how enhanced utilization of glucose and glutamine, with enhanced glutamine-dependent lactate production, promotes cancer cell growth: The WarburQ effect., , , , , , , , и . PLoS Comput. Biol., (2017)GPRuler: Metabolic gene-protein-reaction rules automatic reconstruction., , и . PLoS Comput. Biol., (2021)Machine Learning for Efficient Prediction of Protein Redox Potential: The Flavoproteins Case., , , , , и . J. Chem. Inf. Model., 62 (19): 4748-4759 (2022)Coupling constrained-based flux sampling and clustering to tackle cancer metabolic heterogeneity., , , , , , , и . PDP, стр. 185-192. IEEE, (2023)An Efficient Implementation of Flux Variability Analysis for Metabolic Networks., и . WIVACE, том 1780 из Communications in Computer and Information Science, стр. 58-69. Springer, (2022)Integration of Single-Cell RNA-Sequencing Data into Flux Balance Cellular Automata., , , , , , , и . CIBB, том 12313 из Lecture Notes in Computer Science, стр. 207-215. Springer, (2019)Information Transfer among Coupled Random Boolean Networks., , , , и . ACRI, том 6350 из Lecture Notes in Computer Science, стр. 1-11. Springer, (2010)Recent developments in research on catalytic reaction networks., , , , и . WIVACE, том 130 из EPTCS, стр. 3-13. (2013)The role of backward reactions in a stochastic model of catalytic reaction networks., , , , и . ECAL, стр. 793-801. MIT Press, (2013)The Diffusion of Perturbations in a Model of Coupled Random Boolean Networks., , , , и . ACRI, том 5191 из Lecture Notes in Computer Science, стр. 315-322. Springer, (2008)