From Knowledge, Knowability and the Search for Objective Randomness to a New Vision of Complexity

Herein we consider various concepts of entropy as measures of the complexity of phenomena and in so doing encounter a fundamental problem in physics that affects how we understand the nature of reality. In essence the difficulty has to do with our understanding of randomness, irreversibility and unpredictability using physical theory, and these in turn undermine our certainty regarding what we can and what we cannot know about complex phenomena in general. The sources of complexity examined herein appear to be channels for the amplification of naturally occurring randomness in the physical world. Our analysis suggests that when the conditions for the renormalization group apply, this spontaneous randomness, which is not a reflection of our limited knowledge, but a genuine property of nature, does not realize the conventional thermodynamic state, and a new condition, intermediate between the dynamic and the thermodynamic state, emerges. We argue that with this vision of complexity, life, which with ordinary statistical mechanics seems to be foreign to physics, becomes a natural consequence of dynamical processes.Comment: Phylosophica

Entropic competition in polymeric systems under geometrical confinement

Using molecular dynamics simulation, we investigate the effect of confinement on a system that comprises several stiff segmented polymer chains where each chain has similar segments, but length and stiffness of the segments vary among the chains which makes the system inhomogeneous. The translational and orientational entropy loss due to the confinement plays a crucial role in organizing the chains which can be considered as an entropy-driven segregation mechanism to differentiate the components of the system. Due to the inhomogeneity, both weak and strong confinement regimes show the competition in the system and we see segregation of chains as the confining volume is decreased. In the case of strong spherical confinement, a chain at the periphery shows higher angular mobility than other chains, despite being more radially constrained.Comment: 16 pages, 11 figure

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

Stochastic approach to molecular interactions and computational theory of metabolic and genetic regulations

Binding and unbinding of ligands to specific sites of a macromolecule are one of the most elementary molecular interactions inside the cell that embody the computational processes of biological regulations. The interaction between transcription factors and the operators of genes and that between ligands and binding sites of allosteric enzymes are typical examples of such molecular interactions. In order to obtain the general mathematical framework of biological regulations, we formulate these interactions as finite Markov processes and establish a computational theory of regulatory activities of macromolecules based mainly on graphical analysis of their state transition diagrams. The contribution is summarized as follows: (1) Stochastic interpretation of Michaelis-Menten equation is given. (2) Notion of \textit{probability flow} is introduced in relation to detailed balance. (3) A stochastic analogy of \textit{Wegscheider condition} is given in relation to loops in the state transition diagram. (4) A simple graphical method of computing the regulatory activity in terms of ligands' concentrations is obtained for Wegscheider cases.Comment: 20 pages, 13 figure

On a Simple General Principle of Brain Organization

A possible framework to characterize nervous system dynamics and its organization in conscious and unconscious states is introduced, derived from a high level perspective on the coordinated activity of brain cell ensembles. Some questions are best addressable in a global framework and here we build on past observations about the structure of configurations of brain networks in conscious and unconscious states and about neurophysiological results. Aiming to bind some results together into some sort of coherence with a central theme, the scenario that emerges underscores the crucial importance of the creation and dissipation of energy gradients in brain cellular ensembles resulting in maximization of the configurations in the functional connectivity among those networks that favor conscious awareness and healthy conditions. These considerations are then applied to indicate approaches that can be used to improve neuropathological syndromes.Fil: Perez Velazquez, Jose L.. Ronnin Institute; Estados UnidosFil: Mateos, Diego Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaFil: Guevara Erra, Ramon. Laboratoire Psychologie de la Perception, Cnrs; Franci

Uniting In Silico and In Vivo Systems Biology: a New Concept to Approximate Theory to Real-Life Flux Distributions

Within the last years, bioinformatics expanded from its focus on protein related research to the investigation of whole organisms. Up to date, a variety of bacteria has been modeled, in most detail Escherichia coli. As a systemic approach, flux balance analysis (FBA) has established itself in the scientific community to analyze steady state flux distributions. Within FBA the metabolic network is expressed in terms of a matrix, called the stoichiometric matrix. The assumption of the system to exist in a (temporary) steady state leads to a homogeneous linear system of equations, which is typically underdetermined. By application of an objective function and computation of the linear program that unfolds, one can select one discrete solution out of the existing solution space. In this work, we built a genome based model of the Corynebacterium glutamicum and analyzed it in terms of flux balance analysis. We implemented an enhancement of FBA, called energy balance analysis, that considers thermodynamical issues. We further used metabolic profiling data to impose more constraints on the analyses. By comparing the organism under different environmental conditions, we were able to neglect unknown kinetic constants and to establish new requirements during the energy balance analysis. Namely, we used data derived by raising the C. glutamicum on acetate or glucose. This procedure leads to a further reduction of the solution space and thereby helps to close the gap between predictions and real-life flux distributions. The comprehensive nature of the technique enables it to be applied to any model and to be combined with any other enhancement of the flux balance analysis