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. (2023). Statistical modeling of adaptive neural networks explains co-existence of avalanches and oscillations in resting human brain. Nature Computational Science. Springer Nature. https://doi.org/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. (2019). Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. IOP Publishing. https://doi.org/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. (2018). An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. Elsevier. https://doi.org/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. (2018). Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science and Technology Austria. https://doi.org/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, A. A., Bergmiller, T., Guet, C. C., & Tkačik, G. (2018). Statistical mechanics for metabolic networks during steady state growth. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-018-05417-9
[Published Version] View | Files available | DOI | WoS
 
[8]
2017 | Published | Journal Article | IST-REx-ID: 548 | OA
De Martino, D. (2017). Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. American Physical Society. https://doi.org/10.1103/PhysRevE.96.060401
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
[7]
2017 | Published | Journal Article | IST-REx-ID: 823 | OA
Colabrese, S., De Martino, D., Leuzzi, L., & Marinari, E. (2017). Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa85c3
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[6]
2017 | Published | Journal Article | IST-REx-ID: 947 | OA
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 . American Institute of Physics. https://doi.org/10.1103/PhysRevE.96.010401
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[5]
2017 | Published | Journal Article | IST-REx-ID: 959 | OA
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 . American Institute of Physics. https://doi.org/10.1103/PhysRevE.95.062419
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[4]
2016 | Published | Journal Article | IST-REx-ID: 1260 | OA
De Martino, D. (2016). The dual of the space of interactions in neural network models. International Journal of Modern Physics C. World Scientific Publishing. https://doi.org/10.1142/S0129183116500674
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[3]
2016 | Published | Journal Article | IST-REx-ID: 1394 | OA
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. IOP Publishing Ltd. https://doi.org/10.1088/1478-3975/13/3/036005
[Preprint] View | DOI | Download Preprint (ext.)
 
[2]
2016 | Published | Journal Article | IST-REx-ID: 1188 | OA
De Martino, D., & Masoero, D. (2016). Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth. Journal of Statistical Mechanics: Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa4e8f
[Preprint] View | DOI | Download Preprint (ext.)
 
[1]
2016 | Published | Journal Article | IST-REx-ID: 1485 | OA
De Martino, D. (2016). Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. IOP Publishing Ltd. https://doi.org/10.1088/1478-3975/13/1/016003
[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. (2023). Statistical modeling of adaptive neural networks explains co-existence of avalanches and oscillations in resting human brain. Nature Computational Science. Springer Nature. https://doi.org/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. (2019). Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. IOP Publishing. https://doi.org/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. (2018). An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. Elsevier. https://doi.org/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. (2018). Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science and Technology Austria. https://doi.org/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, A. A., Bergmiller, T., Guet, C. C., & Tkačik, G. (2018). Statistical mechanics for metabolic networks during steady state growth. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-018-05417-9
[Published Version] View | Files available | DOI | WoS
 
[8]
2017 | Published | Journal Article | IST-REx-ID: 548 | OA
De Martino, D. (2017). Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. American Physical Society. https://doi.org/10.1103/PhysRevE.96.060401
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
[7]
2017 | Published | Journal Article | IST-REx-ID: 823 | OA
Colabrese, S., De Martino, D., Leuzzi, L., & Marinari, E. (2017). Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa85c3
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[6]
2017 | Published | Journal Article | IST-REx-ID: 947 | OA
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 . American Institute of Physics. https://doi.org/10.1103/PhysRevE.96.010401
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[5]
2017 | Published | Journal Article | IST-REx-ID: 959 | OA
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 . American Institute of Physics. https://doi.org/10.1103/PhysRevE.95.062419
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[4]
2016 | Published | Journal Article | IST-REx-ID: 1260 | OA
De Martino, D. (2016). The dual of the space of interactions in neural network models. International Journal of Modern Physics C. World Scientific Publishing. https://doi.org/10.1142/S0129183116500674
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[3]
2016 | Published | Journal Article | IST-REx-ID: 1394 | OA
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. IOP Publishing Ltd. https://doi.org/10.1088/1478-3975/13/3/036005
[Preprint] View | DOI | Download Preprint (ext.)
 
[2]
2016 | Published | Journal Article | IST-REx-ID: 1188 | OA
De Martino, D., & Masoero, D. (2016). Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth. Journal of Statistical Mechanics: Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa4e8f
[Preprint] View | DOI | Download Preprint (ext.)
 
[1]
2016 | Published | Journal Article | IST-REx-ID: 1485 | OA
De Martino, D. (2016). Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. IOP Publishing Ltd. https://doi.org/10.1088/1478-3975/13/1/016003
[Preprint] View | DOI | Download Preprint (ext.)
 
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