Abstract
The paper presents a new Information Processing paradigm based on the dynamics encountered in life from organisms as different as Amoebas and the Mammalian brain. Our thesis contemplates that life supports information processing via metabolic dynamics in self-organized enzymatic networks which have the capacity to represent functional catalytic patterns that can be instantiated by speci fic input stimuli. Furthermore, the information patterns can be transferred from the functional dynamics of the metabolic networks to the biochemical enzymatic activity information encoded by DNA. The metabolic dynamics are governed by fractional dynamics that evolve in topological fractal spaces with multi-scale time parameters generating complex attractors. The complete dynamic information process is driven by the short-term process of metabolic dynamics and the long-term process of DNA expression via epigenetic mechanisms.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
