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Quantifying the entropic cost of cellular growth control [article]

Daniele De Martino, Fabrizio Capuani, Andrea De Martino
2017 bioRxiv   pre-print
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 models. Results obtained for E. coli and human cells are consistent with experiments and point to different regulatory strategies by which growth can be fostered or repressed. Moreover we explicitly connect the 'inverse temperature' that controls MaxEnt distributions to the growth dynamics, showing that the initial
more » ... e of a colony may be crucial in determining how an exponentially growing population organizes the phenotypic space.
doi:10.1101/112748 fatcat:wvi75dvszzemhcx33xrqkgioim

Introduction to Modern EW Systems. Edited by Andrea De Martino, Artech House, 2012; 417 pages. Price: £119.00, ISBN 978-1-60807-207-1

Shu-Kun Lin
2013 Sensors  
The following paragraphs are reproduced from the website of the publisher [1]. Master the latest electronic warfare (EW) techniques and technologies related to on-board military platforms with this authoritative resource. You gain expert design guidance on technologies and equipment used to detect and identify emitter threats, giving you an advantage in the never-ending chess game between sensor guided weapons and EW systems. This unique book offers you deeper insight into EW systems principles
more » ... of operation and their mathematical descriptions, arming you with better knowledge for your specific design applications. Moreover, you get practical information on how to counter modern communications data links which provide connectivity and command flow among the armed forces in the battlefield. Taking a sufficiently broad perspective, this comprehensive volume offers you a panoramic view of the various physical domains-RF, Infrared, and electronics-that are present in modern electronic warfare systems. This in-depth book is supported with over 280 illustrations and more than 560 equations.
doi:10.3390/s130101146 fatcat:zq73fdrlyngcdme4usp2okurda

Relationship between fitness and heterogeneity in exponentially growing microbial populations

Anna Paola Muntoni, Alfredo Braunstein, Andrea Pagnani, Daniele De Martino, Andrea De Martino
2022 Biophysical Journal  
Despite major environmental and genetic differences, microbial metabolic networks are known to generate consistent physiological outcomes across vastly different organisms. This remarkable robustness suggests that, at least in bacteria, metabolic activity may be guided by universal principles. The constrained optimization of evolutionarily-motivated objective functions like the growth rate has emerged as the key theoretical assumption for the study of bacterial metabolism. While conceptually
more » ... practically useful in many situations, the idea that certain functions are optimized is hard to validate in data. Moreover, it is not always clear how optimality can be reconciled with the high degree of single-cell variability observed in experiments within microbial populations. To shed light on these issues, we develop an inverse modeling framework that connects the fitness of a population of cells (represented by the mean single-cell growth rate) to the underlying metabolic variability through the Maximum-Entropy inference of the distribution of metabolic phenotypes from data. While no clear objective function emerges, we find that, as the medium gets richer, the fitness and inferred variability for Escherichia coli populations follow and slowly approach the theoretically optimal bound defined by minimal reduction of variability at given fitness. These results suggest that bacterial metabolism may be crucially shaped by a population-level trade-off between growth and heterogeneity.
doi:10.1016/j.bpj.2022.04.012 pmid:35422414 fatcat:wlb5x37wujde7ljspbben2zvwq

Identifying All Moiety Conservation Laws in Genome-Scale Metabolic Networks

Andrea De Martino, Daniele De Martino, Roberto Mulet, Andrea Pagnani, Olivier Lespinet
2014 PLoS ONE  
The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative
more » ... er solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.
doi:10.1371/journal.pone.0100750 pmid:24988199 pmcid:PMC4079565 fatcat:bqjmqnhbnff5lniq7uswekbbsy

The geometrically broken object [article]

Andrea De Martino
1998 arXiv   pre-print
We introduce an analytically solvable model for a fragmented object that, despite of a low degree of randomness and of the extreme simplicity of the breaking process, displays non self-averaging effects in its thermodynamic limit.
arXiv:cond-mat/9805204v1 fatcat:nxcoiq6xc5fcnn6w6op5t33fje

Constraint-based inverse modeling of metabolic networks: a proof of concept [article]

Daniele De Martino, Andrea De Martino
2017 arXiv   pre-print
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 experimental averages are to be retrieved, data are described by a Boltzmann-like distribution (∝ e^F/T) where F is a linear combination of fluxes and the 'temperature' parameter T≥ 0 allows for fluctuations. The zero-temperature limit corresponds to a Flux Balance Analysis scenario, where an objective function (F) is
more » ... d. As a test, we have inverse modeled, by means of Boltzmann learning, the catabolic core of Escherichia coli in glucose-limited aerobic stationary growth conditions. Empirical means are best reproduced when F is a simple combination of biomass production and glucose uptake and the temperature is finite, implying the presence of fluctuations. The scheme presented here has the potential to deliver new quantitative insight on cellular metabolism. Our implementation is however computationally intensive, and highlights the major role that effective algorithms to sample the high-dimensional solution space of metabolic networks can play in this field.
arXiv:1704.08087v1 fatcat:clxkuh3ywzbrrfuzrw7el6kkz4

Relationship between fitness and heterogeneity in exponentially growing microbial populations [article]

Anna Paola Muntoni, Alfredo Braunstein, Andrea Pagnani, Daniele De Martino, Andrea De Martino
2022 arXiv   pre-print
Physical Review E, 93, 012408. [20] De Martino, D., Capuani, F., & De Martino, A. (2016).  ...  John Wiley & Sons. [55] De Martino, D., Capuani, F., Mori, M., De Martino, A., & Marinari, E. (2013).  ... 
arXiv:2104.02594v2 fatcat:wrt2pcynonbfdoajnwxynhflaa

La problématique apocalyptique dans l'anthropologie italienne : de Vittorio Lanternari à Ernesto De Martino

Marcello MASSENZIO, Andrea Alessandri
2013 Archives de Sciences Sociales des Religions  
Presidente dell'Associazione Internazionale Ernesto De Martino Université Tor Vergata de Rome m.massenzio@tiscali.it Avec la collaboration de : Andrea ALESSANDRI Université Tor Vergata de Rome, Département  ...  Voici ce que pense De Martino à ce propos : 3.  ...  En esta presentación, la obra de Lanternari es confrontada a la de su maestro, Raffaelle Pettazzoni, y a la de su colega cercano, Ernesto de Martino.  ... 
doi:10.4000/assr.24871 fatcat:etavldgelbbw3ieiupaycwzwea

Multi-asset minority games [article]

Ginestra Bianconi, Andrea De Martino, Fernando F. Ferreira, Matteo Marsili
2006 arXiv   pre-print
We study analytically and numerically Minority Games in which agents may invest in different assets (or markets), considering both the canonical and the grand-canonical versions. We find that the likelihood of agents trading in a given asset depends on the relative amount of information available in that market. More specifically, in the canonical game players play preferentially in the stock with less information. The same holds in the grand canonical game when agents have positive incentives
more » ... o trade, whereas when agents payoff are solely related to their speculative ability they display a larger propensity to invest in the information-rich asset. Furthermore, in this model one finds a globally predictable phase with broken ergodicity.
arXiv:physics/0603152v1 fatcat:yhox5n7asfe2zkt5mjux2eidna

An introduction to the maximum entropy approach and its application to inference problems in biology

Andrea De Martino, Daniele De Martino
2018 Heliyon  
Acknowledgements We gratefully acknowledge Alfredo Braunstein, Anna Paola Muntoni and Andrea Pagnani for useful insight and suggestions.  ...  the main practical challenges that biological datasets pose to computational and theoretical scientists, whose ultimate goals are interpreting them and using them to build e.g. predictive models and de  ... 
doi:10.1016/j.heliyon.2018.e00596 pmid:29862358 pmcid:PMC5968179 fatcat:3h4fvzybnrcqvptqwc5l36zhzi

Translating ceRNA susceptibilities into correlation functions [article]

Araks Martirosyan, Matteo Marsili, Andrea De Martino
2017 bioRxiv   pre-print
Acknowledgments We gratefully acknowledge Carla Bosia and Andrea Pagnani for useful insight and suggestions.  ...  Martino A.  ...  (B) In specific conditions, an increase in the level of one of the targets can induce a de-repression of the competitor, thereby establishing an effective positive coupling between the targets.  ... 
doi:10.1101/102988 fatcat:icpglqeqnvgmffeqbnrxatp4ny

Quantifying the entropic cost of cellular growth control

Daniele De Martino, Fabrizio Capuani, Andrea De Martino
2017 Physical review. E  
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 models. Results obtained for E. coli and human cells are consistent with experiments and point to different regulatory strategies by which growth can be fostered or repressed. Moreover we explicitly connect the 'inverse temperature' that controls MaxEnt distributions to the growth dynamics, showing that the initial
more » ... e of a colony may be crucial in determining how an exponentially growing population organizes the phenotypic space.
doi:10.1103/physreve.96.010401 pmid:29347168 fatcat:4e344rxccrg4fmassg5tqxkesq

Competing endogenous RNA crosstalk at system level [article]

Mattia Miotto, Enzo Marinari, Andrea De Martino
2019 arXiv   pre-print
microRNAs (miRNAs) regulate gene expression at post-transcriptional level by repressing target RNA molecules. Competition to bind miRNAs tends in turn to correlate their targets, establishing effective RNA-RNA interactions that can influence expression levels, buffer fluctuations and promote signal propagation. Such a potential has been characterized mathematically for small motifs both at steady state and away from stationarity. Experimental evidence, on the other hand, suggests that competing
more » ... endogenous RNA (ceRNA) crosstalk is rather weak. Extended miRNA-RNA networks could however favour the integration of many crosstalk interactions, leading to significant large-scale effects in spite of the weakness of individual links. To clarify the extent to which crosstalk is sustained by the miRNA interactome, we have studied its emergent systemic features in silico in large-scale miRNA-RNA network reconstructions. We show that, although generically weak, system-level crosstalk patterns (i) are enhanced by transcriptional heterogeneities, (ii) can achieve high-intensity even for RNAs that are not co-regulated, (iii) are robust to variability in transcription rates, and (iv) are significantly non-local, i.e. correlate weakly with miRNA-RNA interaction parameters. Furthermore, RNA levels are generically more stable when crosstalk is strongest. As some of these features appear to be encoded in the network's topology, crosstalk may functionally be favoured by natural selection. These results suggest that, besides their repressive role, miRNAs mediate a weak but resilient and context-independent network of cross-regulatory interactions that interconnect the transcriptome, stabilize expression levels and support system-level responses.
arXiv:1910.09256v1 fatcat:3pzszz2om5celiyvkdwawhvylq

Computing fluxes and chemical potential distributions in biochemical networks: energy balance analysis of the human red blood cell [article]

Daniele De Martino, Matteo Figliuzzi, Andrea De Martino, Enzo Marinari
2011 arXiv   pre-print
The analysis of non-equilibrium steady states of biochemical reaction networks relies on finding the configurations of fluxes and chemical potentials satisfying stoichiometric (mass balance) and thermodynamic (energy balance) constraints. Efficient methods to explore such states are crucial to predict reaction directionality, calculate physiologic ranges of variability, estimate correlations, and reconstruct the overall energy balance of the network from the underlying molecular processes.
more » ... different techniques for sampling the space generated by mass balance constraints are currently available, thermodynamics is generically harder to incorporate. Here we introduce a method to sample the free energy landscape of a reaction network at steady state. In its most general form, it allows to calculate distributions of fluxes and concentrations starting from trial functions that may contain prior biochemical information. We apply our method to the human red blood cell's metabolic network, whose space of mass-balanced flux states has been sampled extensively in recent years. Specifically, we profile its thermodynamically feasible flux configurations, characterizing in detail how fluctuations of fluxes and potentials are correlated. Based on this, we derive the cell's energy balance in terms of entropy production, chemical work done and thermodynamic efficiency.
arXiv:1107.2330v1 fatcat:cmtnkqgrmrghfd6cx2sn7w4ebm

Minority games with finite score memory [article]

Damien Challet, Andrea De Martino, Matteo Marsili, Isaac Perez Castillo
2004 arXiv   pre-print
The latter limits indicate that, as is to be expected, for λ > 1 the agent de-activates immediately after the first time step and starts being active and inactive alternatively.  ...  The standard tool for investigating the dynamics of statistical systems with quenched disorder is the pathintegral methodà la De Dominicis, based on the evaluation of the generating functional Z[ψ] =   ... 
arXiv:cond-mat/0407595v1 fatcat:czixx2ck2ndl7d5dkjneo5rf2q
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