Lombardi F, Pepic S, Shriki O, Tkadik G, De Martino D. 2023. Statistical modeling of adaptive neural networks explains co-existence of avalanches and oscillations in resting human brain. Nature Computational Science. 3, 254–263.

De Martino D. 2019. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 52(4), 045002.

De Martino A, De Martino D. 2018. An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. 4(4), e00596.

De Martino D, Mc AA, Bergmiller T, Guet CC, Tkadik G. 2018. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 9(1), 2988.

De Martino D, Tkadik G. 2018. Supporting materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH’, Institute of Science and Technology Austria,10.15479/AT:ISTA:62 .

De Martino D. 2017. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics.  Physical Review E Statistical Nonlinear and Soft Matter Physics . 95(6), 062419.

De Martino D, Capuani F, De Martino A. 2017. Quantifying the entropic cost of cellular growth control.  Physical Review E Statistical Nonlinear and Soft Matter Physics . 96(1), 010401.

Colabrese S, De Martino D, Leuzzi L, Marinari E. 2017. Phase transitions in integer linear problems.  Journal of Statistical Mechanics: Theory and Experiment. 2017(9), 093404.

De Martino D. 2017. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. 96(6), 060401.

De Martino D, Masoero D. 2016. Asymptotic analysis of noisy fitness maximization, applied to metabolism &;amp; growth.  Journal of Statistical Mechanics: Theory and Experiment. 2016(12), 123502.

De Martino D. 2016. The dual of the space of interactions in neural network models. International Journal of Modern Physics C. 27(6), 1650067.

De Martino D, Capuani F, De Martino A. 2016. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. 13(3), 036005.

De Martino D. 2016. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. 13(1), 016003.