Publication | Closed Access
The Epigenetic Algorithm
11
Citations
7
References
2008
Year
Unknown Venue
EngineeringEpigenetic ChangeGeneticsMolecular BiologyEvolutionary AlgorithmsEpigeneticsEvolution StrategyOptimization StrategiesGenetic AlgorithmMetabolic EngineeringEvolution-based MethodEpigenetic AlgorithmDirected EvolutionBiological SystemsBioinformaticsFunctional GenomicsEvolutionary ProgrammingChromatinGenetic AlgorithmsComputational BiologyEpigenomicsGenetic EngineeringSynthetic BiologySystems BiologyMedicine
Evolutionary computation (EC) paradigms are inspired by the optimization strategies utilized by biological systems. While these strategies can be found in every level of biological organization, almost all of the EC techniques which comprise techniques from evolutionary algorithm (EA) to swarm intelligence (SI) have been inspired by organism level optimization strategies. While EA is based on trans-generational genetic adaptation of organisms (biologically inspired), SI is mainly based on intra-generational collective behavioral adaptation of organisms (socially inspired). This paper describes the optimization strategies that bio-molecules utilize both for intra-generational and trans-generational adaptation of biological cells. These adaptive strategies which are known as epigenetic mechanisms emerged long before any other biological strategy and form the basis for Epigenetic algorithms (EGA). Further, the paper proposes an intra-generational EGA based on bio-molecular degradation and autocatalysis which are ubiquitous cellular processes and are pivotal for the adaptive dynamics and evolution of intelligent cellular organization.
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