Daniele De Martino

Tkacik Group

13 Publications

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[13]
2023 | 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. 3, 254–263.
[Published Version] View | Files available | DOI | arXiv
 
[12]
2019 | 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. 52(4), 045002.
[Published Version] View | Files available | DOI | WoS
 
[11]
2018 | 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. 4(4), e00596.
[Published Version] View | Files available | DOI
 
[10]
2018 | Journal Article | IST-REx-ID: 161 | OA
De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. 2018. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 9(1), 2988.
[Published Version] View | Files available | DOI | WoS
 
[9]
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, 10.15479/AT:ISTA:62.
[Published Version] View | Files available | DOI
 
[8]
2017 | 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 . 95(6), 062419.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[7]
2017 | 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 . 96(1), 010401.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[6]
2017 | 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. 2017(9), 093404.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[5]
2017 | 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. 96(6), 060401.
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
[4]
2016 | 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. 2016(12), 123502.
[Preprint] View | DOI | Download Preprint (ext.)
 
[3]
2016 | 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. 27(6), 1650067.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[2]
2016 | 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. 13(3), 036005.
[Preprint] View | DOI | Download Preprint (ext.)
 
[1]
2016 | 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. 13(1), 016003.
[Preprint] View | DOI | Download Preprint (ext.)
 
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13 Publications

Mark all

[13]
2023 | 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. 3, 254–263.
[Published Version] View | Files available | DOI | arXiv
 
[12]
2019 | 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. 52(4), 045002.
[Published Version] View | Files available | DOI | WoS
 
[11]
2018 | 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. 4(4), e00596.
[Published Version] View | Files available | DOI
 
[10]
2018 | Journal Article | IST-REx-ID: 161 | OA
De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. 2018. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 9(1), 2988.
[Published Version] View | Files available | DOI | WoS
 
[9]
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, 10.15479/AT:ISTA:62.
[Published Version] View | Files available | DOI
 
[8]
2017 | 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 . 95(6), 062419.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[7]
2017 | 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 . 96(1), 010401.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[6]
2017 | 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. 2017(9), 093404.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[5]
2017 | 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. 96(6), 060401.
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
[4]
2016 | 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. 2016(12), 123502.
[Preprint] View | DOI | Download Preprint (ext.)
 
[3]
2016 | 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. 27(6), 1650067.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[2]
2016 | 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. 13(3), 036005.
[Preprint] View | DOI | Download Preprint (ext.)
 
[1]
2016 | 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. 13(1), 016003.
[Preprint] View | DOI | Download Preprint (ext.)
 
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Search

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    Citation Style: ISTA Annual Report

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