Daniele De Martino

Tkacik Group

13 Publications

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[13]
2023 | Published | Journal Article | IST-REx-ID: 12762 | OA
Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Statistical modeling of adaptive neural networks explains co-existence of avalanches and oscillations in resting human brain. Nature Computational Science. 2023;3:254-263. doi:10.1038/s43588-023-00410-9
[Published Version] View | Files available | DOI | arXiv
 
[12]
2019 | Published | Journal Article | IST-REx-ID: 6049 | OA
De Martino D. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 2019;52(4). doi:10.1088/1751-8121/aaf2dd
[Published Version] View | Files available | DOI | WoS
 
[11]
2018 | Published | Journal Article | IST-REx-ID: 306 | OA
De Martino A, De Martino D. An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. 2018;4(4). doi:10.1016/j.heliyon.2018.e00596
[Published Version] View | Files available | DOI
 
[10]
2018 | Research Data | IST-REx-ID: 5587 | OA
De Martino D, Tkačik G. Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” 2018. doi:10.15479/AT:ISTA:62
[Published Version] View | Files available | DOI
 
[9]
2018 | Published | Journal Article | IST-REx-ID: 161 | OA
De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-05417-9
[Published Version] View | Files available | DOI | WoS
 
[8]
2017 | Published | Journal Article | IST-REx-ID: 947 | OA
De Martino D, Capuani F, De Martino A. Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;96(1). doi:10.1103/PhysRevE.96.010401
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[7]
2017 | Published | Journal Article | IST-REx-ID: 959 | OA
De Martino D. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;95(6):062419. doi:10.1103/PhysRevE.95.062419
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[6]
2017 | Published | Journal Article | IST-REx-ID: 548 | OA
De Martino D. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. 2017;96(6). doi:10.1103/PhysRevE.96.060401
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
[5]
2017 | Published | Journal Article | IST-REx-ID: 823 | OA
Colabrese S, De Martino D, Leuzzi L, Marinari E. Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. 2017;2017(9). doi:10.1088/1742-5468/aa85c3
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[4]
2016 | Published | Journal Article | IST-REx-ID: 1260 | OA
De Martino D. The dual of the space of interactions in neural network models. International Journal of Modern Physics C. 2016;27(6). doi:10.1142/S0129183116500674
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[3]
2016 | Published | Journal Article | IST-REx-ID: 1485 | OA
De Martino D. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. 2016;13(1). doi:10.1088/1478-3975/13/1/016003
[Preprint] View | DOI | Download Preprint (ext.)
 
[2]
2016 | Published | Journal Article | IST-REx-ID: 1394 | OA
De Martino D, Capuani F, De Martino A. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. 2016;13(3). doi:10.1088/1478-3975/13/3/036005
[Preprint] View | DOI | Download Preprint (ext.)
 
[1]
2016 | Published | Journal Article | IST-REx-ID: 1188 | OA
De Martino D, Masoero D. Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth. Journal of Statistical Mechanics: Theory and Experiment. 2016;2016(12). doi:10.1088/1742-5468/aa4e8f
[Preprint] View | DOI | Download Preprint (ext.)
 
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13 Publications

Mark all

[13]
2023 | Published | Journal Article | IST-REx-ID: 12762 | OA
Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Statistical modeling of adaptive neural networks explains co-existence of avalanches and oscillations in resting human brain. Nature Computational Science. 2023;3:254-263. doi:10.1038/s43588-023-00410-9
[Published Version] View | Files available | DOI | arXiv
 
[12]
2019 | Published | Journal Article | IST-REx-ID: 6049 | OA
De Martino D. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 2019;52(4). doi:10.1088/1751-8121/aaf2dd
[Published Version] View | Files available | DOI | WoS
 
[11]
2018 | Published | Journal Article | IST-REx-ID: 306 | OA
De Martino A, De Martino D. An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. 2018;4(4). doi:10.1016/j.heliyon.2018.e00596
[Published Version] View | Files available | DOI
 
[10]
2018 | Research Data | IST-REx-ID: 5587 | OA
De Martino D, Tkačik G. Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” 2018. doi:10.15479/AT:ISTA:62
[Published Version] View | Files available | DOI
 
[9]
2018 | Published | Journal Article | IST-REx-ID: 161 | OA
De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-05417-9
[Published Version] View | Files available | DOI | WoS
 
[8]
2017 | Published | Journal Article | IST-REx-ID: 947 | OA
De Martino D, Capuani F, De Martino A. Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;96(1). doi:10.1103/PhysRevE.96.010401
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[7]
2017 | Published | Journal Article | IST-REx-ID: 959 | OA
De Martino D. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;95(6):062419. doi:10.1103/PhysRevE.95.062419
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[6]
2017 | Published | Journal Article | IST-REx-ID: 548 | OA
De Martino D. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. 2017;96(6). doi:10.1103/PhysRevE.96.060401
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
[5]
2017 | Published | Journal Article | IST-REx-ID: 823 | OA
Colabrese S, De Martino D, Leuzzi L, Marinari E. Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. 2017;2017(9). doi:10.1088/1742-5468/aa85c3
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[4]
2016 | Published | Journal Article | IST-REx-ID: 1260 | OA
De Martino D. The dual of the space of interactions in neural network models. International Journal of Modern Physics C. 2016;27(6). doi:10.1142/S0129183116500674
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[3]
2016 | Published | Journal Article | IST-REx-ID: 1485 | OA
De Martino D. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. 2016;13(1). doi:10.1088/1478-3975/13/1/016003
[Preprint] View | DOI | Download Preprint (ext.)
 
[2]
2016 | Published | Journal Article | IST-REx-ID: 1394 | OA
De Martino D, Capuani F, De Martino A. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. 2016;13(3). doi:10.1088/1478-3975/13/3/036005
[Preprint] View | DOI | Download Preprint (ext.)
 
[1]
2016 | Published | Journal Article | IST-REx-ID: 1188 | OA
De Martino D, Masoero D. Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth. Journal of Statistical Mechanics: Theory and Experiment. 2016;2016(12). doi:10.1088/1742-5468/aa4e8f
[Preprint] View | DOI | Download Preprint (ext.)
 
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