Choon Yee Wen, Mohamad Mohd Saberi, Deris Safaai, Illias Rosli Md
Int J Data Min Bioinform. 2014;10(2):225-38. doi: 10.1504/ijdmb.2014.064016.
The development of microbial production system has become popular in recent years as microbial hosts offer a number of unique advantages for both native and heterologous small-molecules. However, the main drawback is low yield or productivity of the desired products. Optimisation algorithms are implemented in previous works to identify the effects of gene knockout. Nevertheless, the previous works faced performance issue. Thus, a hybrid of Bees Algorithm and Flux Balance Analysis (BAFBA) is proposed in this paper to improve the performance in predicting optimal sets of gene deletion for maximising the growth rate and production yield of certain metabolite. This paper involves two datasets which are E. coli and S. cerevisiae. The list of knockout genes, growth rate and production yield after the deletion are the results from the experiments. BAFBA presents better results compared to the other methods and the identified list may be useful in solving genetic engineering problems.
近年来，微生物生产系统的发展备受关注，因为微生物宿主对于天然和异源小分子具有许多独特优势。然而，主要缺点是所需产物的产量或生产率较低。先前的研究工作中实施了优化算法来确定基因敲除的影响。尽管如此，先前的工作面临性能问题。因此，本文提出了一种蜜蜂算法与通量平衡分析的混合方法（BAFBA），以提高预测最佳基因缺失集的性能，从而最大化特定代谢物的生长速率和产量。本文涉及两个数据集，即大肠杆菌和酿酒酵母。敲除基因列表、敲除后的生长速率和产量是实验结果。与其他方法相比，BAFBA呈现出更好的结果，并且所确定的列表可能有助于解决基因工程问题。
