Increase in Complexity and Information through Molecular Evolution

Entropy and institutional theory

Purpose

Once introduced and conceptualized as a factor that causes erosion and decay of social institutions and subsequent deinstitutionalization, the notion of entropy is at odds with predictions of institutional isomorphism and seems to directly contradict the tendency toward ever-increasing institutionalization. The purpose of this paper is to offer a resolution of this theoretical inconsistency by revisiting the meaning of entropy and reconceptualizing institutionalization from an information-theoretic point of view.

Design/methodology/approach

It is a theoretical paper that offers an information perspective on institutionalization.

Findings

A mistaken understanding of the nature and role of entropy in the institutional theory is caused by conceptualizing it as a force that counteracts institutional tendencies and acts in opposite direction. Once institutionalization and homogeneity are seen as a product of natural tendencies in the organizational field, the role of entropy becomes clear. Entropy manifests itself at the level of information processing and corresponds with increasing uncertainty and the decrease of the value of information. Institutionalization thus can be seen as a special case of an increase in entropy and a decrease of knowledge. Institutionalization is a state of maximum entropy.

Originality/value

It is explained why institutionalization and institutional persistence are what to be expected in the long run and why information entropy contributes to this tendency. Contrary to the tenets of the institutional work perspective, no intentional efforts of individuals and collective actors are needed to maintain institutions. In this respect, the paper contributes to the view of institutional theory as a theory of self-organization.

Fitness optimization and evolution of permanent replicator systems

In this paper, we discuss fitness landscape evolution of permanent replicator systems applying the hypothesis that the specific time of evolutionary adaptation of system parameters is much slower than the time of internal evolutionary dynamics. In other words, we suppose that the extremal principle of Darwinian evolution based on Fisher's fundamental theorem of natural selection is valid for the steady-states of permanent replicator systems. Various cases illustrating this concept are considered.

Science-Driven Societal Transformation, Part I: Worldview

Humanity faces serious social and environmental problems, including climate change and biodiversity loss. Increasingly, scientists, global policy experts, and the general public conclude that incremental approaches to reduce risk are insufficient and transformative change is needed across all sectors of society. However, the meaning of transformation is still unsettled in the literature, as is the proper role of science in fostering it. This paper is the first in a three-part series that adds to the discussion by proposing a novel science-driven research-and-development program aimed at societal transformation. More than a proposal, it offers a perspective and conceptual framework from which societal transformation might be approached. As part of this, it advances a formal mechanics with which to model and understand self-organizing societies of individuals. While acknowledging the necessity of reform to existing societal systems (e.g., governance, economic, and financial systems), the focus of the series is on transformation understood as systems change or systems migration—the de novo development of and migration to new societal systems. The series provides definitions, aims, reasoning, worldview, and a theory of change, and discusses fitness metrics and design principles for new systems. This first paper proposes a worldview, built using ideas from evolutionary biology, complex systems science, cognitive sciences, and information theory, which is intended to serve as the foundation for the R&D program. Subsequent papers in the series build on the worldview to address fitness metrics, system design, and other topics.

Structure of proteins: Evolution with unsolved mysteries

Evolution of macromolecules could be considered as a milestone in the history of life. Nucleic acids are the long stretches of nucleotides that contain all the possible codes and information of life. On the other hand, proteins are their actual translated outcomes, or reflections of modifications in their structure that have occurred at a slow, but steady rate over a very long period of evolution. Over the years of research, biophysicists, biochemists, molecular and structural biologists have unfurled several layers of the structural convolutions in these chemical molecules; however evolutionists look over their structures through a different prism, which may or may not coincide with others. There remains a need to outline several well-known, but less discussed features of protein structures, like intrinsically disordered states, degron signals and different types of ubiquitin chains providing degradation signals, which help the cellular proteolytic machinery to identify and target the proteins towards degradation pathways. There are several important factors, which are critical for folding of proteins into their native three-dimensional conformations by the cytoplasmic chaperones; but in real time how the chaperones fold the newly synthesized polypeptide sequences into a particular three-dimensional shape within a fraction of second is still a mystery for biologists as well as mathematicians. Multiple similar unsolved or unaddressed questions need to be addressed in detail so that future line of research can dig deeper into the finer details of these structures of the proteins.

Self-organization and information in biosystems: a case study

Eigen's original molecular evolution equations are extended in two ways. (1) By an additional nonlinear autocatalytic term leading to new stability features, their dependence on the relative size of fitness parameters and on initial conditions is discussed in detail. (2) By adding noise terms that represent the spontaneous generation of molecules by mutations of substrate molecules, these terms are taken care of by both Langevin and Fokker-Planck equations. The steady-state solution of the latter provides us with a potential landscape giving a bird's eye view on all stable states (attractors). Two different types of evolutionary processes are suggested: (a) in a fixed attractor landscape and (b) caused by a changed landscape caused by changed fitness parameters. This may be related to Gould's concept of punctuated equilibria. External signals in the form of additional molecules may generate a new initial state within a specific basin of attraction. The corresponding attractor is then reached by self-organization. This approach allows me to define pragmatic information as signals causing a specific reaction of the receiver and to use equations equivalent to (1) as model of (human) pattern recognition as substantiated by the synergetic computer.

Molecular evolution between chemistry and biology : The interplay of competition, cooperation, and mutation

Biological evolution is reduced to three fundamental processes in the spirit of a minimal model: (i) Competition caused by differential fitness, (ii) cooperation of competitors in the sense of symbiosis, and (iii) variation introduced by mutation understood as error-prone reproduction. The three combinations of two fundamental processes each, ([Formula: see text]) competition and mutation, ([Formula: see text]) cooperation and competition, and ([Formula: see text]) cooperation and mutation, are analyzed. Changes in population dynamics that are induced by bifurcations and threshold phenomena are discussed.