3,942 research outputs found
The dual of the space of interactions in neural network models
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 perspective. By means of duality arguments an integer
linear system is defined whose solution space is the dual of the Gardner space
and whose solutions represent mutually unstable patterns. We propose and
discuss Monte Carlo methods in order to find and remove unstable patterns and
uniformly sample the space of interactions thereafter. We illustrate the
problem on a set of real data and perform ensemble calculation that shows how
the emergence of phase dominated by unstable patterns can be triggered in a
non-linear discontinuous way.Comment: 13 pages, 4 figures, 1 tabl
A Van-Der-Waals picture for metabolic networks from MaxEnt modeling: inherent bistability and elusive coexistence
In this work maximum entropy distributions in the space of steady states of
metabolic networks are defined upon constraining the first and second moment of
the growth rate. Inherent bistability of fast and slow phenotypes, akin to a
Van-Der Waals picture, emerges upon considering control on the average growth
(optimization/repression) and its fluctuations (heterogeneity). This is applied
to the carbon catabolic core of E.coli where it agrees with some stylized facts
on the persisters phenotype and it provides a quantitative map with metabolic
fluxes, opening for the possibility to detect coexistence from flux data.
Preliminary analysis on data for E.Coli cultures in standard conditions shows,
on the other hand, degeneracy for the inferred parameters that extend in the
coexistence region.Comment: 9 pages, 4 figure
The free lunch of a scale-free metabolism
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 thermodynamically unfeasible cycles, that
are unbounded by physical constraints and would be able to perform work without
expenditure of free energy. After correcting for thermodynamics, the metabolic
space scales meaningfully with the physical limiting factors, acquiring in turn
a richer multimodal structure potentially leading to symmetry breaking while
optimizing for objective functions.Comment: Comments are welcom
Quantifying the entropic cost of cellular growth control
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 size of a colony may be crucial in
determining how an exponentially growing population organizes the phenotypic
space.Comment: 3 page
Quantitative constraint-based computational model of tumor-to-stroma coupling via lactate shuttle
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 in the presence
of oxygen, to the secretion of carbon equivalents (usually in the form of lactate) in the cell’s
surroundings, a feature known as the Warburg effect. While the molecular basis of this phenomenon
are still to be elucidated, it is clear that the spilling of energy resources contributes to creating a
peculiar microenvironment for tumors, possibly characterized by a degree of toxicity. This suggests
that mechanisms for recycling the fermentation products (e.g. a lactate shuttle) may be active,
effectively inducing a mutually beneficial metabolic coupling between aberrant and non-aberrant
cells. Here we analyze this scenario through a large-scale in silico metabolic model of interacting
human cells. By going beyond the cell-autonomous description, we show that elementary physico-
chemical constraints indeed favor the establishment of such a coupling under very broad conditions.
The characterization we obtained by tuning the aberrant cell’s demand for ATP, amino-acids and
fatty acids and/or the imbalance in nutrient partitioning provides quantitative support to the idea
that synergistic multi-cell effects play a central role in cancer sustainmen
Asymptotic analysis of noisy fitness maximization, applied to metabolism and growth
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. In the asymptotic regime of slow diffusion, that
coincides with the relevant experimental range, the resulting non-linear
Fokker-Planck equation is solved for the steady state in the WKB approximation
that maps it into the ground state of a quantum particle in an Airy potential
plus a centrifugal term. We retrieve scaling laws for growth rate fluctuations
and time response with respect to the distance from the maximum growth rate
suggesting that suboptimal populations can have a faster response to
perturbations.Comment: 24 pages, 6 figure
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