Self-Organization of Population Structure in Biological Systems

Author(s):  
Guy A. Hoelzer
2018 ◽  
Vol 5 (4) ◽  
pp. 110 ◽  
Author(s):  
Kazusa Beppu ◽  
Ziane Izri ◽  
Yusuke Maeda ◽  
Ryota Sakamoto

As expressed “God made the bulk; the surface was invented by the devil” by W. Pauli, the surface has remarkable properties because broken symmetry in surface alters the material properties. In biological systems, the smallest functional and structural unit, which has a functional bulk space enclosed by a thin interface, is a cell. Cells contain inner cytosolic soup in which genetic information stored in DNA can be expressed through transcription (TX) and translation (TL). The exploration of cell-sized confinement has been recently investigated by using micron-scale droplets and microfluidic devices. In the first part of this review article, we describe recent developments of cell-free bioreactors where bacterial TX-TL machinery and DNA are encapsulated in these cell-sized compartments. Since synthetic biology and microfluidics meet toward the bottom-up assembly of cell-free bioreactors, the interplay between cellular geometry and TX-TL advances better control of biological structure and dynamics in vitro system. Furthermore, biological systems that show self-organization in confined space are not limited to a single cell, but are also involved in the collective behavior of motile cells, named active matter. In the second part, we describe recent studies where collectively ordered patterns of active matter, from bacterial suspensions to active cytoskeleton, are self-organized. Since geometry and topology are vital concepts to understand the ordered phase of active matter, a microfluidic device with designed compartments allows one to explore geometric principles behind self-organization across the molecular scale to cellular scale. Finally, we discuss the future perspectives of a microfluidic approach to explore the further understanding of biological systems from geometric and topological aspects.


Author(s):  
Margaret A. Boden

Artificial life (A-Life) models biological systems. Like AI, it has both technological and scientific aims. ‘Robots and artificial life’ explains that A-Life is integral to AI, because all the intelligence we know about is found in living organisms. AI technologists turn to biology in developing practical applications of many kinds, including robots, evolutionary programming, and self-organizing devices. Robots are quintessential examples of AI, having high visibility and being hugely ingenious—and very big business, too. Evolutionary AI, although widely used, is less well known. Self-organizing machines are even less familiar. Nevertheless, in the quest to understand self-organization, AI has been as useful to biology as biology has been to AI.


2015 ◽  
Vol 4 (2) ◽  
pp. 65-74
Author(s):  
Гавриленко ◽  
T. Gavrilenko ◽  
Еськов ◽  
Valeriy Eskov ◽  
Еськов ◽  
...  

There are several criteria in science for stationarity (stability) of different dynamical systems. The stationarity in physics, engineering and chemistry is being interpreted as matching the requirements of dx/dt=0, where x=x(t) - is the vector of system’s state, or the equality of distribution functions f(x) for different samples which characterize the system. However, in case of social or biological systems the matching of the requirements is impossible and there is a problem of specific assessment of stationary regimes of complex systems of the third type. The possibility of studying of such systems within the frame of deterministic chaos, stochastic approach and theory of chaos and self-organization is being discussed. This article explains why I.R. Prigogine refused from materialistic (in fact deterministic) approach in the description of such special systems of third type and tried to get away from the traditional science in the description of biological systems.


2009 ◽  
Vol 17 (3) ◽  
pp. 653-676 ◽  
Author(s):  
Joanna Raczaszek-Leonardi

The paper draws a parallel between natural language symbols and the symbolic mode in living systems. The inextricability of symbols and the dynamics with which they are functionally related shows that much of their structuring is due to dynamics and self-organization. It is also stressed that important factors that determine the shape of language structure lie outside individual mind/brains and they draw on time-scales quite different from those of phenomenological experience. Analysis of language into units and subsystems is thus not straightforward, since they show functionality on many levels and many time-scales. Finally it is recognized that, as a specific and specialized system of inter-individual coordination, natural language is many hierarchical levels away form simpler forms of information transmission in biological systems.


2021 ◽  
Vol 12 ◽  
pp. 433
Author(s):  
Zaid Aljuboori

Biological systems are complex with distinct characteristics such as nonlinearity, adaptability, and self-organization. Biomedical research has helped in advancing our understanding of certain components the human biology but failed to illustrate the behavior of the biological systems within. This failure can be attributed to the use of the linear approach, which reduces the system to its components then study each component in isolation. This approach assumes that the behavior of complex systems is the result of the sum of the function of its components. The complex systems approach requires the identification of the components of the system and their interactions with each other and with the environment. Within neurosurgery, this approach has the potential to advance our understanding of the human nervous system and its subsystems.


1990 ◽  
Vol 30 (2) ◽  
pp. 39-44
Author(s):  
Yasuji SAWADA ◽  
Mika SATO ◽  
Tomoaki ITAYAMA

Author(s):  
Scott Camazine ◽  
Jean-Louis Deneubourg ◽  
Nigel R. Franks ◽  
James Sneyd ◽  
Guy Theraula ◽  
...  

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