Daniele De Martino
Tkacik Group
13 Publications
2023 | Published | Journal Article | IST-REx-ID: 12762 |

Lombardi, Fabrizio, Selver Pepic, Oren Shriki, Gašper Tkačik, and Daniele De Martino. “Statistical Modeling of Adaptive Neural Networks Explains Co-Existence of Avalanches and Oscillations in Resting Human Brain.” Nature Computational Science. Springer Nature, 2023. https://doi.org/10.1038/s43588-023-00410-9.
[Published Version]
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| arXiv
2019 | Published | Journal Article | IST-REx-ID: 6049 |

De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical and Theoretical. IOP Publishing, 2019. https://doi.org/10.1088/1751-8121/aaf2dd.
[Published Version]
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| DOI
| WoS
2018 | Published | Journal Article | IST-REx-ID: 306 |

De Martino, Andrea, and Daniele De Martino. “An Introduction to the Maximum Entropy Approach and Its Application to Inference Problems in Biology.” Heliyon. Elsevier, 2018. https://doi.org/10.1016/j.heliyon.2018.e00596.
[Published Version]
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| DOI
2018 | Research Data | IST-REx-ID: 5587 |

De Martino, Daniele, and Gašper Tkačik. “Supporting Materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:62.
[Published Version]
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2018 | Published | Journal Article | IST-REx-ID: 161 |

De Martino, Daniele, Andersson Anna Mc, Tobias Bergmiller, Calin C Guet, and Gašper Tkačik. “Statistical Mechanics for Metabolic Networks during Steady State Growth.” Nature Communications. Springer Nature, 2018. https://doi.org/10.1038/s41467-018-05417-9.
[Published Version]
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| Files available
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| WoS
2017 | Published | Journal Article | IST-REx-ID: 548 |

De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by Constraining Growth-Rate Moments Predicts Coexistence of Phenotypes.” Physical Review E. American Physical Society, 2017. https://doi.org/10.1103/PhysRevE.96.060401.
[Submitted Version]
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2017 | Published | Journal Article | IST-REx-ID: 823 |

Colabrese, Simona, Daniele De Martino, Luca Leuzzi, and Enzo Marinari. “Phase Transitions in Integer Linear Problems.” Journal of Statistical Mechanics: Theory and Experiment. IOPscience, 2017. https://doi.org/10.1088/1742-5468/aa85c3.
[Submitted Version]
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| WoS
2017 | Published | Journal Article | IST-REx-ID: 947 |

De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Quantifying the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.96.010401.
[Submitted Version]
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| WoS
2017 | Published | Journal Article | IST-REx-ID: 959 |

De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary Metabolic Network Models via Thermodynamics.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.95.062419.
[Submitted Version]
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2016 | Published | Journal Article | IST-REx-ID: 1260 |

De Martino, Daniele. “The Dual of the Space of Interactions in Neural Network Models.” International Journal of Modern Physics C. World Scientific Publishing, 2016. https://doi.org/10.1142/S0129183116500674.
[Preprint]
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| arXiv
2016 | Published | Journal Article | IST-REx-ID: 1394 |

De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Growth against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.” Physical Biology. IOP Publishing Ltd., 2016. https://doi.org/10.1088/1478-3975/13/3/036005.
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2016 | Published | Journal Article | IST-REx-ID: 1188 |

De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy Fitness Maximization, Applied to Metabolism & Growth.” Journal of Statistical Mechanics: Theory and Experiment. IOPscience, 2016. https://doi.org/10.1088/1742-5468/aa4e8f.
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2016 | Published | Journal Article | IST-REx-ID: 1485 |

De Martino, Daniele. “Genome-Scale Estimate of the Metabolic Turnover of E. Coli from the Energy Balance Analysis.” Physical Biology. IOP Publishing Ltd., 2016. https://doi.org/10.1088/1478-3975/13/1/016003.
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13 Publications
2023 | Published | Journal Article | IST-REx-ID: 12762 |

Lombardi, Fabrizio, Selver Pepic, Oren Shriki, Gašper Tkačik, and Daniele De Martino. “Statistical Modeling of Adaptive Neural Networks Explains Co-Existence of Avalanches and Oscillations in Resting Human Brain.” Nature Computational Science. Springer Nature, 2023. https://doi.org/10.1038/s43588-023-00410-9.
[Published Version]
View
| Files available
| DOI
| arXiv
2019 | Published | Journal Article | IST-REx-ID: 6049 |

De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical and Theoretical. IOP Publishing, 2019. https://doi.org/10.1088/1751-8121/aaf2dd.
[Published Version]
View
| Files available
| DOI
| WoS
2018 | Published | Journal Article | IST-REx-ID: 306 |

De Martino, Andrea, and Daniele De Martino. “An Introduction to the Maximum Entropy Approach and Its Application to Inference Problems in Biology.” Heliyon. Elsevier, 2018. https://doi.org/10.1016/j.heliyon.2018.e00596.
[Published Version]
View
| Files available
| DOI
2018 | Research Data | IST-REx-ID: 5587 |

De Martino, Daniele, and Gašper Tkačik. “Supporting Materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:62.
[Published Version]
View
| Files available
| DOI
2018 | Published | Journal Article | IST-REx-ID: 161 |

De Martino, Daniele, Andersson Anna Mc, Tobias Bergmiller, Calin C Guet, and Gašper Tkačik. “Statistical Mechanics for Metabolic Networks during Steady State Growth.” Nature Communications. Springer Nature, 2018. https://doi.org/10.1038/s41467-018-05417-9.
[Published Version]
View
| Files available
| DOI
| WoS
2017 | Published | Journal Article | IST-REx-ID: 548 |

De Martino, Daniele. “Maximum Entropy Modeling of Metabolic Networks by Constraining Growth-Rate Moments Predicts Coexistence of Phenotypes.” Physical Review E. American Physical Society, 2017. https://doi.org/10.1103/PhysRevE.96.060401.
[Submitted Version]
View
| DOI
| Download Submitted Version (ext.)
2017 | Published | Journal Article | IST-REx-ID: 823 |

Colabrese, Simona, Daniele De Martino, Luca Leuzzi, and Enzo Marinari. “Phase Transitions in Integer Linear Problems.” Journal of Statistical Mechanics: Theory and Experiment. IOPscience, 2017. https://doi.org/10.1088/1742-5468/aa85c3.
[Submitted Version]
View
| DOI
| Download Submitted Version (ext.)
| WoS
2017 | Published | Journal Article | IST-REx-ID: 947 |

De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Quantifying the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.96.010401.
[Submitted Version]
View
| DOI
| Download Submitted Version (ext.)
| WoS
2017 | Published | Journal Article | IST-REx-ID: 959 |

De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary Metabolic Network Models via Thermodynamics.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.95.062419.
[Submitted Version]
View
| DOI
| Download Submitted Version (ext.)
| WoS
2016 | Published | Journal Article | IST-REx-ID: 1260 |

De Martino, Daniele. “The Dual of the Space of Interactions in Neural Network Models.” International Journal of Modern Physics C. World Scientific Publishing, 2016. https://doi.org/10.1142/S0129183116500674.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2016 | Published | Journal Article | IST-REx-ID: 1394 |

De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Growth against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.” Physical Biology. IOP Publishing Ltd., 2016. https://doi.org/10.1088/1478-3975/13/3/036005.
[Preprint]
View
| DOI
| Download Preprint (ext.)
2016 | Published | Journal Article | IST-REx-ID: 1188 |

De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy Fitness Maximization, Applied to Metabolism & Growth.” Journal of Statistical Mechanics: Theory and Experiment. IOPscience, 2016. https://doi.org/10.1088/1742-5468/aa4e8f.
[Preprint]
View
| DOI
| Download Preprint (ext.)
2016 | Published | Journal Article | IST-REx-ID: 1485 |

De Martino, Daniele. “Genome-Scale Estimate of the Metabolic Turnover of E. Coli from the Energy Balance Analysis.” Physical Biology. IOP Publishing Ltd., 2016. https://doi.org/10.1088/1478-3975/13/1/016003.
[Preprint]
View
| DOI
| Download Preprint (ext.)