Evolving Turing Machines for Biosequence Recognition and Analysis

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{vallejo:2001:EuroGP,

• author = "Edgar E. Vallejo and Fernando Ramos",
• title = "Evolving {Turing} Machines for Biosequence Recognition and Analysis",
• booktitle = "Genetic Programming, Proceedings of EuroGP'2001",
• year = "2001",
• editor = "Julian F. Miller and Marco Tomassini and Pier Luca Lanzi and Conor Ryan and Andrea G. B. Tettamanzi and William B. Langdon",
• volume = "2038",
• series = "LNCS",
• pages = "192--203",
• address = "Lake Como, Italy",
• publisher_address = "Berlin",
• month = "18-20 " # apr,
• organisation = "EvoNET",
• publisher = "Springer-Verlag",
• keywords = "genetic algorithms, genetic programming, Bioinformatics, DNA, Turing machines, Multiple Sequence aligment",
• ISBN = "3-540-41899-7",
• DOI = "doi:10.1007/3-540-45355-5_15",
• size = "12 pages",
• abstract = "This article presents a genetic programming system for biosequence recognition and analysis. In our model, a population of Turing machines evolves the capability of biosequence recognition using genetic algorithms. We use HIV sequences as the working example. Experimental results indicate that evolved Turing machines are capable of recognizing HIV sequences in a collection of training sets. In addition, we demonstrate that the evolved Turing machines can be used to approximate the multiple sequence alignment problem.",
• notes = "EuroGP'2001, part of \cite{miller:2001:gp}",

}

Genetic Programming entries for Edgar E Vallejo Fernando Ramos Quintana

Citations