DocumentCode :
2911002
Title :
An effective mutation-based measure for evaluating the suitability of parental sequences to undergo DNA shuffling experiments
Author :
Montera, Luciana ; do Carmo Nicoletti, Maria ; Silva, Flavio Henrique da ; Moscato, Pablo
Author_Institution :
PPG-Biotechnol., Univ. Federal de Sao Carlos, Sao Carlos
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
765
Lastpage :
772
Abstract :
The DNA shuffling process has been successfully used in many experiments of Directed Molecular Evolution. In a shuffling experiment genes are recombined by an iterative procedure of PCR cycles aiming at obtaining new genes, hopefully with some of the original functions being improved. The optimizations of the parameters involved in the process as well as the characteristics of the parental sequences are of extreme importance to guarantee the success of a shuffling experiment. This paper proposes a new measure, based on the number of bases between existing mutations in the parental sequences, suitable for evaluating the suitability of two sequences to be submitted to a DNA shuffling experiment. In order to investigate the usefulness of the proposed mutation-based measure versus two commonly used measures, a family of 37 DNA gene sequences codifying for snake venom metallopeptidases was used for evaluation purposes using the three measures. The parental sequences identified by each of the three measures were validated by simulating the DNA shuffling process using the software eShuffle. The eShuffle results illustrate on the benefits of the mutation-based measure proposed in this paper.
Keywords :
DNA; biology computing; genetic algorithms; genetics; iterative methods; molecular biophysics; proteins; DNA gene sequences; DNA shuffling experiments; DNA shuffling process; PCR cycles; directed molecular evolution; eShuffle; iterative procedure; mutation-based measure; parental sequences; snake venom metallopeptidases; DNA; Evolutionary computation; Sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
Type :
conf
DOI :
10.1109/CEC.2008.4630882
Filename :
4630882
Link To Document :
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