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 adapt...
Classical genetic programming (GP) solves problems by applying the Darwinian concepts of selection, ...
Abstract: Biochemical networks are the backbones of physiological systems of organisms. Therefore, a...
Current use of microbes for metabolic engineering suffers from loss of metabolic output due to natur...
Evolutionary computation (EC) paradigms are inspired by the optimization strategies utilized by biol...
Evolutionary Computation (EC) paradigms are inspired by the optimization strategies utilized by biol...
Evolutionary computation is a group of biologically inspired algorithms used to solve complex optimi...
This dissertation describes how to improve automated design and evolution in computers using the str...
Recent efforts toward a Darwinian psychology of human behavior will profit from taking account of pr...
Abbreviated Abstract: The objective of Evolutionary Computation is to solve practical problems (e.g....
Evolutionary algorithms (EAs) are a set of optimization and machine learning techniques that find th...
International audienceDNA is not the sole medium by which parents transmit information to their offs...
In recent times computational algorithms inspired by biological processes and evolution are gaining ...
How complex traits arise within organisms over evolutionary time is an important question that has r...
Abstract. Extending the notion of inheritable genotype in genetic programming (GP) from the common m...
The systems approach to genomics seeks quantitative and predictive descriptions of cells and organis...
Classical genetic programming (GP) solves problems by applying the Darwinian concepts of selection, ...
Abstract: Biochemical networks are the backbones of physiological systems of organisms. Therefore, a...
Current use of microbes for metabolic engineering suffers from loss of metabolic output due to natur...
Evolutionary computation (EC) paradigms are inspired by the optimization strategies utilized by biol...
Evolutionary Computation (EC) paradigms are inspired by the optimization strategies utilized by biol...
Evolutionary computation is a group of biologically inspired algorithms used to solve complex optimi...
This dissertation describes how to improve automated design and evolution in computers using the str...
Recent efforts toward a Darwinian psychology of human behavior will profit from taking account of pr...
Abbreviated Abstract: The objective of Evolutionary Computation is to solve practical problems (e.g....
Evolutionary algorithms (EAs) are a set of optimization and machine learning techniques that find th...
International audienceDNA is not the sole medium by which parents transmit information to their offs...
In recent times computational algorithms inspired by biological processes and evolution are gaining ...
How complex traits arise within organisms over evolutionary time is an important question that has r...
Abstract. Extending the notion of inheritable genotype in genetic programming (GP) from the common m...
The systems approach to genomics seeks quantitative and predictive descriptions of cells and organis...
Classical genetic programming (GP) solves problems by applying the Darwinian concepts of selection, ...
Abstract: Biochemical networks are the backbones of physiological systems of organisms. Therefore, a...
Current use of microbes for metabolic engineering suffers from loss of metabolic output due to natur...