Anomalous Diffusion within the Transcriptome as a Bio-Inspired Computing Framework for Resilience

Abstract

Much of biology-inspired computer science is based on the Central Dogma, as implemented with genetic algorithms or evolutionary computation. That 60-year-old biological principle based on the genome, transcriptome and proteasome is becoming overshadowed by a new paradigm of complex ordered associations and connections between layers of biological entities, such as interactomes, metabolomics, etc. We define a new hierarchical concept as the "Connectosome", and propose new venues of computational data structures based on a conceptual framework called "Grand Ensemble" which contains the Central Dogma as a subset. Connectedness and communication within and between living or biology-inspired systems comprise ensembles from which a physical computing system can be conceived. In this framework the delivery of messages is filtered by size and a simple and rapid semantic analysis of their content. This work aims to initiate discussion on the Grand Ensemble in network biology as a representation of a Persistent Turing Machine. This framework adding interaction and persistency to the classic Turing-machine model uses metrics based on resilience that has application to dynamic optimization problem solving in Genetic Programming.

Molecular simulations of cellular processes

“…They have also advanced computational methods to parameterize automatically realistic models, such as the evolutionary algorithms (Trovato and Tozzini 2012;Leonarski et al 2013;Seffens 2017) or to access equilibrium and dynamical properties of both the solute and the solvent (Ayton et al 2007;McGuffee and Elcock 2010;Mereghetti and Wade 2012;Dama et al 2013;Elcock 2013;Zhou 2013, 2016;Trovato et al 2013;Ciccotti and Ferrario 2013;Trovato and Tozzini 2014;Ozer et al 2015;Wang and Brady 2016).…”