Placement of unique restriction sites in synthetic genomes using multi-objective optimization

Author

Sharmin, Mahfuza ; Rahman, M. Sohel

Author_Institution

Dept. of CSE, Bangladesh Univ. of Eng. & Technol., Dhaka, Bangladesh

fYear

2012

fDate

4-7 Oct. 2012

Firstpage

1

Lastpage

4

Abstract

Placing unique restriction sites in synthetic genomes is computationally hard problem. This paper targets to apply variants of genetic algorithm to modify virus length genomes to introduce a large number of evenly spaced unique restriction sites while preserving their amino-acid sequence. From our experimental results we show that genetic algorithms, considering multiple objectives non-linearly, give better results than traditional heuristic methods and local search methods.

Keywords

biology computing; genetic algorithms; genomics; molecular configurations; search problems; amino acid sequence; computationally hard problems; genetic algorithm; heuristic methods; local search methods; multiobjective optimization; multiple objectives; restriction sites; synthetic genomes; virus length genomes; Biochemistry; Genetic algorithms; Genomics; Optimization; Sociology; Sorting; Statistics; Genetic algorithms; Multiobjective optimization; Restriction enzyme; Synthetic biology;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine (BIBM), 2012 IEEE International Conference on

Conference_Location

Philadelphia, PA

Print_ISBN

978-1-4673-2559-2

Electronic_ISBN

978-1-4673-2558-5

Type

conf

DOI

10.1109/BIBM.2012.6392635

Filename

6392635