密码子使用偏好性
有向无环图
基因
计算机科学
算法
明星(博弈论)
生物
遗传密码
遗传算法
遗传学
A*搜索算法
基因组
编码(内存)
序列(生物学)
计算生物学
作者
Xiaowu Liu,Ronghai Deng,Jinwen Wang,Xunzhang Wang
标识
DOI:10.1016/j.jtbi.2013.11.022
摘要
Codon optimized genes have two major advantages: they simplify de novo gene synthesis and increase the expression level in target hosts. Often they achieve this by altering codon usage in a given gene. Codon optimization is complex because it usually needs to achieve multiple opposing goals. In practice, finding an optimal sequence from the massive number of possible combinations of synonymous codons that can code for the same amino acid sequence is a challenging task. In this article, we introduce COStar, a D-star Lite-based dynamic search algorithm for codon optimization. The algorithm first maps the codon optimization problem into a weighted directed acyclic graph using a sliding window approach. Then, the D-star Lite algorithm is used to compute the shortest path from the start site to the target site in the resulting graph. Optimizing a gene is thus converted to a search in real-time for a shortest path in a generated graph. Using in silico experiments, the performance of the algorithm was shown by optimizing the different genes including the human genome. The results suggest that COStar is a promising codon optimization tool for de novo gene synthesis and heterologous gene expression.
科研通智能强力驱动
Strongly Powered by AbleSci AI