The algorithmic beauty of plants
The algorithmic beauty of plants
A Standard GA Approach to Native Protein Conformation Prediction
Proceedings of the 6th International Conference on Genetic Algorithms
On Genetic Algorithms and Lindenmayer Systems
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Multimeme Algorithms for Protein Structure Prediction
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Modelling Blood Vessels of the Eye with Parametric L-Systems Using Evolutionary Algorithms
AIMDM '99 Proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
Coevolution Produces an Arms Race among Virtual Plants
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
Grammatical Evolution: Evolving Programs for an Arbitrary Language
EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
Grammatical evolution to design fractal curves with a given dimension
IBM Journal of Research and Development
On hopeful monsters, neutral networks and junk code in evolving L-systems
Proceedings of the 10th annual conference on Genetic and evolutionary computation
A tale of human-competitiveness in bioinformatics
ACM SIGEVOlution
Competition and evolution in virtual plant communities: a new modeling approach
Natural Computing: an international journal
Folding protein-like structures with open L-systems
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
A critical view of the evolutionary design of self-assembling systems
EA'05 Proceedings of the 7th international conference on Artificial Evolution
Incorporating knowledge of secondary structures in a l-system-based encoding for protein folding
EA'05 Proceedings of the 7th international conference on Artificial Evolution
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
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A protein is a linear chain of amino acids that folds into a unique functional structure, called its native state. In this state, proteins show repeated substructures like alpha helices and beta sheets. This suggests that native structures may be captured by the formalism known as Lindenmayer systems (L-systems). In this paper an evolutionary approach is used as the inference procedure for folded structures on simple lattice models. The algorithm searches the space of L-systems which are then executed to obtain the phenotype, thus our approach is close to Grammatical Evolution. The problem is to find a set of rewriting rules that represents a target native structure on the lattice model. The proposed approach has produced promising results for short sequences. Thus the foundations are set for a novel encoding based on L-systems for evolutionary approaches to both the Protein Structure Prediction and Inverse Folding Problems.