60 citations · 405 across the 30 of their papers we have counts for
31 papers
Storing Infinite Dynamical Attractors in Nonreciprocal Associative Neural Networks
Miguel Aguilera, Daniele De Martino
We develop a dynamical mean-field theory for nonreciprocal associative networks that store an extensive number of dynamical attractors, from limit cycles to strange attractors. Usi…
Synchronization, Kinematic Waves and Spike-Phase-Separation in Feedback Ising Neural Networks on Heterogeneous Graphs
Anna Poggialini, Irem Topal, Fabrizio Lombardi +1
Structural heterogeneity constrains collective dynamics in complex systems. However, its analytical tractability out of equilibrium remains limited. In this work, we study a class…
Single-cell metabolic flux analysis reveals coexisting optimal sub-groups, cross-feeding, and mixotrophy in a cyanobacterial population
Arián Ferrero-Fernández, Paula Prondzinsky, Lucia Gastoldi +5
We derive a single-cell level understanding of metabolism in an isogenic cyanobacterial population by integrating secondary ion mass spectrometry (SIMS) derived multi-isotope uptak…
Metabolic coordination and phase transitions in spatially distributed multi-cellular systems
Krishnadev Narayanankutty, José Antonio Pereiro-Morejon, Arián Ferrero-Fernández +7
During overflow metabolism, cells excrete glycolytic byproducts when growing under aerobic conditions in a seemingly wasteful fashion. While potentially advantageous for microbes w…
Emergence of collective self-oscillations in minimal lattice models with feedback
Dmitry Sinelschikov, Anna Poggialini, Maria Francesca Abbate +1
The emergence of collective oscillations and synchronization is a widespread phenomenon in complex systems. While widely studied in dynamical systems theory, this phenomenon is not…
Modelling spatial constraints and scaling effects of catalyst phase separation on linear pathway kinetics
Nino Lauber, Ondrej Tichacek, Krishnadev Narayanankutty +2
Chemical reactions are usually studied under the assumption that both substrates and catalysts are well mixed (WM) throughout the system. Although this is often applicable to test-…
Statistical modeling of adaptive neural networks explains coexistence of avalanches and oscillations in resting human brain
Fabrizio Lombardi, Selver Pepić, Oren Shriki +2
Neurons in the brain are wired into adaptive networks that exhibit a range of collective dynamics. Oscillations, for example, are paradigmatic synchronous patterns of neural activi…
Relationship between fitness and heterogeneity in exponentially growing microbial populations
Anna Paola Muntoni, Alfredo Braunstein, Andrea Pagnani +2
Despite major environmental and genetic differences, microbial metabolic networks are known to generate consistent physiological outcomes across vastly different organisms. This re…
Oscillations in feedback driven systems: thermodynamics and noise
Daniele De Martino, Andre C Barato
Oscillations in nonequilibrium noisy systems are important physical phenomena. These oscillations can happen in autonomous biochemical oscillators such as circadian clocks. They ca…
Phase transitions in integer linear problems
S. Colabrese, D. De Martino, L. Leuzzi +1
The resolution of linear system with positive integer variables is a basic yet difficult computational problem with many applications. We consider sparse uncorrelated random system…
Constraint-based inverse modeling of metabolic networks: a proof of concept
Daniele De Martino, Andrea De Martino
We consider the problem of inferring the probability distribution of flux configurations in metabolic network models from empirical flux data. For the simple case in which experime…
Statistical mechanics for metabolic networks during steady-state growth
Daniele De Martino, Anna MC Andersson, Tobias Bergmiller +2
Which properties of metabolic networks can be derived solely from stoichiometric information about the network's constituent reactions? Predictive results have been obtained by Flu…
The free lunch of a scale-free metabolism
Daniele De Martino
In this work it is shown that scale free tails in metabolic flux distributions inferred from realistic large scale models can be simply an artefact due to reactions involved in the…
Quantifying the entropic cost of cellular growth control
Daniele De Martino, Fabrizio Capuani, Andrea De Martino
We quantify the amount of regulation required to control growth in living cells by a Maximum Entropy approach to the space of underlying metabolic states described by genome-scale…
Asymptotic analysis of noisy fitness maximization, applied to metabolism and growth
Daniele De Martino, Davide Masoero
We consider a population dynamics model coupling cell growth to a diffusion in the space of metabolic phenotypes as it can be obtained from realistic constraints-based modelling. I…
Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli
Daniele De Martino, Fabrizio Capuani, Andrea De Martino
The solution space of genome-scale models of cellular metabolism provides a map between physically viable flux configurations and cellular metabolic phenotypes described, at the mo…
Quantitative constraint-based computational model of tumor-to-stroma coupling via lactate shuttle
Fabrizio Capuani, Daniele De Martino, Enzo Marinari +1
Cancer cells utilize large amounts of ATP to sustain growth, relying primarily on non-oxidative, fermentative pathways for its production. In many types of cancers this leads, even…
Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis
Daniele De Martino
In this article the notion of metabolic turnover is revisited in the light of recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo methods we perform an exa…
The dual of the space of interactions in neural network models
Daniele De Martino
In this work the Gardner problem of inferring interactions and fields for an Ising neural network from given patterns under a local stability hypothesis is addressed under a dual p…
Inferring metabolic phenotypes from the exometabolome through a thermodynamic variational principle
Daniele De Martino, Fabrizio Capuani, Andrea De Martino
Networks of biochemical reactions, like cellular metabolic networks, are kept in non-equilibrium steady states by the exchange fluxes connecting them to the environment. In most ca…
Overelaxed hit-and-run Monte Carlo for the uniform sampling of convex bodies with applications in metabolic network analysis
G. De Concini, D. De Martino
The uniform sampling of convex regions in high dimension is an important computational issue, from both theoretical and applied point of view. The hit-and-run montecarlo algorithms…
Uniform sampling of steady states in metabolic networks: heterogeneous scales and rounding
Daniele De Martino, Matteo Mori, Valerio Parisi
The uniform sampling of convex polytopes is an interesting computational problem with many applications in inference from linear constraints, but the performances of sampling algor…
Counting and correcting thermodynamically infeasible flux cycles in genome-scale metabolic networks
Daniele De Martino, Fabrizio Capuani, Matteo Mori +2
Thermodynamics constrains the flow of matter in a reaction network to occur through routes along which the Gibbs energy decreases, implying that viable steady-state flux patterns s…
Identifying all irreducible conserved metabolite pools in genome-scale metabolic networks: a general method and the case of Escherichia coli
A. De Martino, D. De Martino, R. Mulet +1
The stoichiometry of metabolic networks usually gives rise to a family of conservation laws for the aggregate concentration of specific pools of metabolites, which not only constra…