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Thermodynamics and Information Theory of Living Systems

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A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Entropy and Biology".

Deadline for manuscript submissions: closed (31 July 2020) | Viewed by 26955

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Special Issue Editors

Dr. Bernat Corominas-Murtra

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Guest Editor

Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
Interests: biophysics; information theory; stem cells; statistical mechanics; networks

Dr. Artemy Kolchinsky

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Guest Editor

Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
Interests: information theory; thermodynamics of computation; stochastic thermodynamics; complex systems; biosemiotics

Prof. Rudolf Hanel

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Guest Editor

1. Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria;
2. Complexity Science Hub Vienna Josefstädter Strasse 39, A-1080 Vienna, Austria
Interests: information theory; non-equilibrium statistical mechanics; non-linear dynamics; complex systems

Special Issue Information

Dear Colleagues,

One of the defining features of living systems is their ability to process, exchange and store large amounts of information at multiple levels of organization, ranging from the biochemical to the ecological. At the same time, living entities are non-equilibrium—possibly at criticality—physical systems that continuously exchange matter and energy with structured environments, all while obeying the laws of thermodynamics. These properties not only lead to the emergence of biological information, but also impose constraints and trade-offs on the costs of such information processing. Some of these costs arise due to the particular properties of the material substrate of living matter in which information processing takes place, while others are universal and apply to all physical systems that process information.

In the past decade, the relationship between thermodynamics and information has received renewed scientific attention, attracting an increasing number of researchers and achieving significant progress. Despite this, the field is full of open problems and challenges at all levels, especially when dealing with biological systems. In spite of these difficulties, continued progress has the potential to fundamentally shape our future understanding of biology.

In this Special Issue we encourage researchers from theoretical biology, statistical physics, neuroscience, information theory, and complex systems to present their research on the connection between thermodynamics and information, with special emphasis on their implications for biological phenomena. We welcome contributions that focus on a particular biological system, as well as contributions that propose general theoretical approaches. We also welcome contributions that use mathematical techniques from statistical physics (variational methods, fluctuation theorems, uncertainty relations, etc.) to investigate biological questions.

Dr. Bernat Corominas-Murtra
Dr. Artemy Kolchinsky
Prof. Rudolf Hanel
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

biophysics
stochastic thermodynamics
thermodynamics of information
information theory of living systems
non-equilibrium thermodynamics
thermodynamics of living systems
information processing in living systems

Published Papers (7 papers)

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Research

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17 pages, 5564 KiB

Open AccessArticle

Tropical Monsoon Forest Thermodynamics Based on Remote Sensing Data

by Robert Sandlersky

Entropy 2020, 22(11), 1226; https://doi.org/10.3390/e22111226 - 28 Oct 2020

Cited by 1 | Viewed by 2083

Abstract

This paper addresses thermodynamic variables that characterize the energy balance and structure of the solar energy transformation by the ecosystems of deciduous tropical forests. By analyzing the seasonal dynamics of these variables, two main states of the thermodynamic system are determined: the end of the drought season and the end of the wet season. Two sub-systems of solar energy transformation are also defined: a balance system that is responsible for the moisture transportation between the ecosystem and atmosphere; and a structural bioproductional system responsible for biological productivity. Several types of thermodynamic systems are determined based on the ratio between the invariants of the variables. They match the main classes of the landscape cover. A seasonal change of thermodynamic variables for different types of thermodynamic systems is additionally studied. The study reveals that temperature above the forest ecosystems is about 4° lower than above the open areas during most of the year. Full article

(This article belongs to the Special Issue Thermodynamics and Information Theory of Living Systems)

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57 pages, 3576 KiB

Open AccessArticle

Intrinsic and Extrinsic Thermodynamics for Stochastic Population Processes with Multi-Level Large-Deviation Structure

by Eric Smith

Entropy 2020, 22(10), 1137; https://doi.org/10.3390/e22101137 - 07 Oct 2020

Cited by 6 | Viewed by 2957

Abstract

A set of core features is set forth as the essence of a thermodynamic description, which derive from large-deviation properties in systems with hierarchies of timescales, but which are not dependent upon conservation laws or microscopic reversibility in the substrate hosting the process. The most fundamental elements are the concept of a macrostate in relation to the large-deviation entropy, and the decomposition of contributions to irreversibility among interacting subsystems, which is the origin of the dependence on a concept of heat in both classical and stochastic thermodynamics. A natural decomposition that is known to exist, into a relative entropy and a housekeeping entropy rate, is taken here to define respectively the intensive thermodynamics of a system and an extensive thermodynamic vector embedding the system in its context. Both intensive and extensive components are functions of Hartley information of the momentary system stationary state, which is information about the joint effect of system processes on its contribution to irreversibility. Results are derived for stochastic chemical reaction networks, including a Legendre duality for the housekeeping entropy rate to thermodynamically characterize fully-irreversible processes on an equal footing with those at the opposite limit of detailed-balance. The work is meant to encourage development of inherent thermodynamic descriptions for rule-based systems and the living state, which are not conceived as reductive explanations to heat flows. Full article

(This article belongs to the Special Issue Thermodynamics and Information Theory of Living Systems)

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22 pages, 3240 KiB

Open AccessFeature PaperArticle

A Multi-Scale Approach to Modeling E. coli Chemotaxis

by Eran Agmon and Ryan K. Spangler

Entropy 2020, 22(10), 1101; https://doi.org/10.3390/e22101101 - 29 Sep 2020

Cited by 7 | Viewed by 4099

Abstract

The degree to which we can understand the multi-scale organization of cellular life is tied to how well our models can represent this organization and the processes that drive its evolution. This paper uses Vivarium—an engine for composing heterogeneous computational biology models into integrated, multi-scale simulations. Vivarium’s approach is demonstrated by combining several sub-models of biophysical processes into a model of chemotactic E. coli that exchange molecules with their environment, express the genes required for chemotaxis, swim, grow, and divide. This model is developed incrementally, highlighting cross-compartment mechanisms that link E. coli to its environment, with models for: (1) metabolism and transport, with transport moving nutrients across the membrane boundary and metabolism converting them to useful metabolites, (2) transcription, translation, complexation, and degradation, with stochastic mechanisms that read real gene sequence data and consume base pairs and ATP to make proteins and complexes, and (3) the activity of flagella and chemoreceptors, which together support navigation in the environment. Full article

(This article belongs to the Special Issue Thermodynamics and Information Theory of Living Systems)

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22 pages, 3947 KiB

Open AccessEditor’s ChoiceArticle

TMEA: A Thermodynamically Motivated Framework for Functional Characterization of Biological Responses to System Acclimation

by Kevin Schneider, Benedikt Venn and Timo Mühlhaus

Entropy 2020, 22(9), 1030; https://doi.org/10.3390/e22091030 - 15 Sep 2020

Cited by 4 | Viewed by 3225

Abstract

The objective of gene set enrichment analysis (GSEA) in modern biological studies is to identify functional profiles in huge sets of biomolecules generated by high-throughput measurements of genes, transcripts, metabolites, and proteins. GSEA is based on a two-stage process using classical statistical analysis to score the input data and subsequent testing for overrepresentation of the enrichment score within a given functional coherent set. However, enrichment scores computed by different methods are merely statistically motivated and often elusive to direct biological interpretation. Here, we propose a novel approach, called Thermodynamically Motivated Enrichment Analysis (TMEA), to account for the energy investment in biological relevant processes. Therefore, TMEA is based on surprisal analysis, which offers a thermodynamic-free energy-based representation of the biological steady state and of the biological change. The contribution of each biomolecule underlying the changes in free energy is used in a Monte Carlo resampling procedure resulting in a functional characterization directly coupled to the thermodynamic characterization of biological responses to system perturbations. To illustrate the utility of our method on real experimental data, we benchmark our approach on plant acclimation to high light and compare the performance of TMEA with the most frequently used method for GSEA. Full article

(This article belongs to the Special Issue Thermodynamics and Information Theory of Living Systems)

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10 pages, 222 KiB

Open AccessArticle

Answering Schrödinger’s “What Is Life?”

by Stuart Kauffman

Entropy 2020, 22(8), 815; https://doi.org/10.3390/e22080815 - 25 Jul 2020

Cited by 23 | Viewed by 6659

Abstract

In his “What Is Life?” Schrödinger poses three questions: (1) What is the source of order in organisms? (2) How do organisms remain ordered in the face of the Second Law of Thermodynamics? (3) Are new laws of physics required? He answers his first question with his famous “aperiodic solid”. He leaves his second and third questions unanswered. I try to show that his first answer is also the answer to his second question. Aperiodic solids such as protein enzymes are “boundary conditions” that constrain the release of energy into a few degrees of freedom in non-equilibrium processes such that thermodynamic work is done. This work propagates and builds structures and controls processes. These constitute his causally efficacious “code script” controlling development. The constrained release of energy also delays the production of entropy that can be exported from cells as it forms. Therefore, cells remain ordered. This answers his second question. However, “What is life?” must also ask about the diachronic evolution of life. Here, the surprising answer to this extended version of Schrödinger’s third question is that there are no new entailing laws of physics. No laws at all entail the evolution of ours or any biosphere. Full article

(This article belongs to the Special Issue Thermodynamics and Information Theory of Living Systems)

17 pages, 5866 KiB

Open AccessArticle

Optimal Encoding in Stochastic Latent-Variable Models

by Michael E. Rule, Martino Sorbaro and Matthias H. Hennig

Entropy 2020, 22(7), 714; https://doi.org/10.3390/e22070714 - 28 Jun 2020

Cited by 4 | Viewed by 2863

Abstract

In this work we explore encoding strategies learned by statistical models of sensory coding in noisy spiking networks. Early stages of sensory communication in neural systems can be viewed as encoding channels in the information-theoretic sense. However, neural populations face constraints not commonly considered in communications theory. Using restricted Boltzmann machines as a model of sensory encoding, we find that networks with sufficient capacity learn to balance precision and noise-robustness in order to adaptively communicate stimuli with varying information content. Mirroring variability suppression observed in sensory systems, informative stimuli are encoded with high precision, at the cost of more variable responses to frequent, hence less informative stimuli. Curiously, we also find that statistical criticality in the neural population code emerges at model sizes where the input statistics are well captured. These phenomena have well-defined thermodynamic interpretations, and we discuss their connection to prevailing theories of coding and statistical criticality in neural populations. Full article

(This article belongs to the Special Issue Thermodynamics and Information Theory of Living Systems)

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Review

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22 pages, 542 KiB

Open AccessReview

Fate of Duplicated Neural Structures

by Luís F. Seoane

Entropy 2020, 22(9), 928; https://doi.org/10.3390/e22090928 - 25 Aug 2020

Cited by 2 | Viewed by 3993

Abstract

Statistical physics determines the abundance of different arrangements of matter depending on cost-benefit balances. Its formalism and phenomenology percolate throughout biological processes and set limits to effective computation. Under specific conditions, self-replicating and computationally complex patterns become favored, yielding life, cognition, and Darwinian evolution. Neurons and neural circuits sit at a crossroads between statistical physics, computation, and (through their role in cognition) natural selection. Can we establish a statistical physics of neural circuits? Such theory would tell what kinds of brains to expect under set energetic, evolutionary, and computational conditions. With this big picture in mind, we focus on the fate of duplicated neural circuits. We look at examples from central nervous systems, with stress on computational thresholds that might prompt this redundancy. We also study a naive cost-benefit balance for duplicated circuits implementing complex phenotypes. From this, we derive phase diagrams and (phase-like) transitions between single and duplicated circuits, which constrain evolutionary paths to complex cognition. Back to the big picture, similar phase diagrams and transitions might constrain I/O and internal connectivity patterns of neural circuits at large. The formalism of statistical physics seems to be a natural framework for this worthy line of research. Full article

(This article belongs to the Special Issue Thermodynamics and Information Theory of Living Systems)

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