Incorporating Knowledge of Secondary Structures in a L-System-Based Encoding for Protein Folding

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{Ochoa:2005:EA,

• author = "Gabriela Ochoa and Gabi Escuela and Natalio Krasnogor",
• title = "Incorporating Knowledge of Secondary Structures in a L-System-Based Encoding for Protein Folding",
• booktitle = "7th International Conference on Artificial Evolution EA 2005",
• year = "2005",
• editor = "El-Ghazali Talbi and Pierre Liardet and Pierre Collet and Evelyne Lutton and Marc Schoenauer",
• volume = "3871",
• series = "Lecture Notes in Computer Science",
• pages = "247--258",
• address = "Lille, France",
• month = oct # " 26-28",
• publisher = "Springer",
• note = "Revised Selected Papers",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-540-33589-4",
• URL = "http://www.cs.stir.ac.uk/~goc/papers/LsysPFPEA05.pdf",
• DOI = "doi:10.1007/11740698_22",
• size = "12 pages",
• abstract = "An encoding scheme for protein folding on lattice models, inspired by parametric L-systems, was proposed. The encoding incorporates problem domain knowledge in the form of predesigned production rules that capture commonly known secondary structures: alpha-helices and beta-sheets. The ability of this encoding to capture protein native conformations was tested using an evolutionary algorithm as the inference procedure for discovering L-systems. Results confirmed the suitability of the proposed representation. It appears that the occurrence of motifs and sub-structures is an important component in protein folding, and these sub-structures may be captured by a grammar-based encoding. This line of research suggests novel and compact encoding schemes for protein folding that may have practical implications in solving meaningful problems in biotechnology such as structure prediction and protein folding.",
• notes = "published 2006",

}

Genetic Programming entries for Gabriela Ochoa Gabi Escuela Natalio Krasnogor

Citations