New Approach to Control of the Dissolved Oxygen Concentration in a Biomass-Driven Self-Cycling Biochemical Process

Kasperski, Andrzej; Sun, Kaibiao; Tian, Yuan

doi:10.1080/00986445.2014.948113

Cited by 2 publications

(1 citation statement)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Unified cell bioenergetics allows the universal interpretation of several main cell bioenergetic effects (inter alia, the Pasteur, Crabtree, Kluyver, glucose effects) that can occur during bioprocesses and certain diseases (diabetes, cancer, heart diseases) based on the intramitochondrial NADH (mtNADH) level [19][20][21][22][23][24][25]. Mitochondria control both the life and death of cells [19,26].…”

Section: Introductionmentioning

confidence: 99%

Genome Attractors as Places of Evolution and Oases of Life

Kasperski

2021

Processes

Self Cite

View full text Add to dashboard Cite

So far, much effort has been made to understand evolution and life phenomena. However, the more we know, the more new puzzles appear. This article introduces some new approaches to understanding what drives evolution. Organism evolution has been examined using artificial neural networks and a semihomologous approach based on the sequences of cytochrome c. To realize this task, three and four-layer neural networks have been designed and then taught. It has been shown that the four-layer neural network more clearly recognizes evolutionary similarities, usually indicating greater (comparing to the three-layer network) similarities to the organisms that were used to train the neural networks. It has been noted that unified cell bioenergetics allows describing the manner in which the main engine that drives evolution works. Reasons for some diseases have been also interpreted to present considerations in a broader and more holistic view. The presented results point out that the evolution of organisms can be considered as a discontinuous process taking place mainly in genome attractors that define and stabilize organisms.

show abstract