A hybrid of bees algorithm and flux balance analysis (BAFBA) for the optimisation of microbial strains

Yee Wen Choon, Mohd Saberi Mohamad, Safaai Deris, Rosli Md Illias

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)225-238
Number of pages14
JournalInternational Journal of Data Mining and Bioinformatics
Issue number2
Publication statusPublished - 2014
Externally publishedYes


  • Bees algorithm
  • Bioinformatics
  • Data mining
  • Flux balance analysis
  • Gene knockout
  • Metabolic engineering
  • Microbial strains
  • Optimisation

ASJC Scopus subject areas

  • Information Systems
  • General Biochemistry,Genetics and Molecular Biology
  • Library and Information Sciences


Dive into the research topics of 'A hybrid of bees algorithm and flux balance analysis (BAFBA) for the optimisation of microbial strains'. Together they form a unique fingerprint.

Cite this