Energy rate density as a complexity metric and evolutionary driver

Chaisson, Eric J.

doi:10.1002/cplx.20323

Cited by 82 publications

(63 citation statements)

References 26 publications

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“…This article reiterates and extends a proposed hypothesis that specific energy flow constitutes a complexity metric and potential evolutionary driver, most recently assessed in what is hereafter called Paper I [1]. There, I probed broadly, deeply, and phenomenologically the scenario of cosmic evolution-a scientific study of sequential change writ large, from big bang to humankind, over the course of 14 Gy of natural history.…”

mentioning

confidence: 83%

Energy rate density. II. Probing further a new complexity metric

Chaisson

2011

Complexity

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Appraisal of the concept of energy rate density continues, as both a potential quantitative metric for complexity studies and a key feature of a unifying hypothesis for the origin and evolution of material systems throughout Nature writ large. This article extends a recent study reported in this journal, hereby analyzing normalized energy flows for an array of complex systems experiencing physical, biological, and cultural evolution. The results strengthen the comprehensive scenario of cosmic evolution in broad and general ways yet with much deep, empirical evidence.

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mentioning

confidence: 83%

Energy rate density. II. Probing further a new complexity metric

Chaisson

2011

Complexity

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“…An energy-based metric was proposed by Chaisson [60] measuring the energy rate density, where Φm is energy rate density, E is energy flow through a system, τ is the time frame, and m is system mass. Chaisson obtains results that correlate well with other notions of complexity, and below we add our proposed relation from this transcriptome model framework Φm ¼ E=τm or which we propose is :…”

Section: Measuring Complexitymentioning

confidence: 99%

Models of RNA Interaction from Experimental Datasets: Framework of Resilience

Seffens¹

2017

Applications of RNA-Seq and Omics Strategies - From Microorganisms to Human Health

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Resilience is a network property of systems responding under stress, which for biomedicine correlates to chronic or acute insults. Current need exists for models and algorithms to study whole transcriptome differences between tissues and disease states to understand resilience. Goal of this effort is to interpret cellular transcription in a dynamic system biology framework of RNA molecules forming an information structure with regulatory properties acting on individual transcripts. We develop and evaluate a bioinformatics framework based on information theory that utilizes RNA expression data to create a whole transcriptome model of interaction that could lead to the discovery of new biological control mechanisms. This addresses a fundamental question as to why transcription yields such a small fraction of protein products. We focus on a transformative concept that individual transcripts collectively form an "information cloud" of sequence words, which for some genes may have significant regulatory impact. Extending the concept of cis-and trans-regulation, we propose to search for RNAs that are modulated by interactions with the transcriptome cloud and calling such examples nebula regulation. This framework has implications as a paradigm change for RNA regulation and provides a deeper understanding of nucleotide sequence structure and -omic language meaning.

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“…When there is nowhere to go but up, some species will go up. Other scientists (Rubi 2008;Smart 2009;Chaisson 2011) argue that evolution is invariably driven toward progress by certain inescapable processes, among them basic laws of physics. Rubi (2008) claims that order emerges from chaos where there is excess energy-as with Earth's open system with regard to the sun's energy (thus countering the inevitable increase in entropy from the second law of thermodynamics)-and therefore complexity arises in living systems because of this favorable energy gradient.…”

Section: Do Thermodynamics and Energy Flow Lead To Inevitable Evolutimentioning

confidence: 99%

“…Rubi (2008) claims that order emerges from chaos where there is excess energy-as with Earth's open system with regard to the sun's energy (thus countering the inevitable increase in entropy from the second law of thermodynamics)-and therefore complexity arises in living systems because of this favorable energy gradient. Chaisson (2011) argues that energy rate density, a measure of how much energy flows through each gram of a system per second (Chorost 2012), is a universal gauge to quantify the complexity of ordered systems. Analysis of energy rate density, he contends, reveals an unequivocal upward trend in complexity concomitant with the "ascension" of life from microbes to humans and from hunter-gatherers to technological societies.…”

Section: Do Thermodynamics and Energy Flow Lead To Inevitable Evolutimentioning

confidence: 99%

Avoiding the Pitfall of Progress and Associated Perils of Evolutionary Education

Werth

2012

Evo Edu Outreach

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People reflexively see all change as implying inevitably increasing progress and complexity. This expected directionality is especially observed in students' views of living things, with some species envisioned as "higher" or more evolved. Students tend naturally to see all evolutionary change as adaptive, progressive, optimal, and teleological, with improvement achieved as needed or desired by organisms (if not as planned in advance). Following an extended outline of many interrelated ways, this basic yet unfortunately widespread and deep-seated misconception of evolutionary thinking ensnares students and hinders proper understanding of the actual pattern and process of evolution, a more useful pedagogical approach is presented. A strategy that involves eliciting preconceptions, engaging in numerous counterexamples, and continually reinforcing an alternative view is generally effective. This is best achieved by tackling the misconception of progress head-on, with an active learning model that forces students to come up with substitute explanations. Several examples of exercises and activities to combat the universal and automatically intuitive inclination toward teleological notions of progress are given, including analyses of paleontology, ecology, biochemistry, development, and systematics.

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Energy rate density as a complexity metric and evolutionary driver

Cited by 82 publications

References 26 publications

Energy rate density. II. Probing further a new complexity metric

Energy rate density. II. Probing further a new complexity metric

Models of RNA Interaction from Experimental Datasets: Framework of Resilience

Avoiding the Pitfall of Progress and Associated Perils of Evolutionary Education

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