Sandhu Kuljeet Singh, Pandey Sunil, Maiti Souvik, Pillai Beena
GN Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology, Mall Road, Delhi, India.
In Silico Biol. 2008;8(2):187-92.
Codon optimization is a generic technique to achieve optimum expression of a foreign gene in the host's cell system. Selection of optimum codons depends on codon usage of the host genome and the presence of several desirable and undesirable sequence motifs. Searching these motifs in all possible combinations of the codons increases the search space exponentially with respect to sequence length. GASCO is an algorithm developed for the optimum codon selection using genetic algorithms. The algorithm reduces the search space and provides an approximate solution to the problem. The algorithm has applications in DNA vaccine design for successfully eliciting potent immune responses and synthetic gene design for metabolic pathway engineering. The software for the proposed algorithm is available on http://miracle.igib.res.in/gasco/.
密码子优化是一种在宿主细胞系统中实现外源基因最佳表达的通用技术。最佳密码子的选择取决于宿主基因组的密码子使用情况以及几种期望和不期望的序列基序的存在。在密码子的所有可能组合中搜索这些基序会使搜索空间相对于序列长度呈指数增长。GASCO是一种使用遗传算法开发的用于最佳密码子选择的算法。该算法减少了搜索空间并为该问题提供了近似解决方案。该算法在DNA疫苗设计中可成功引发强效免疫反应，在代谢途径工程的合成基因设计中也有应用。所提出算法的软件可在http://miracle.igib.res.in/gasco/上获取。
