PACBB 2016: 10th International Conference on Practical Applications of Computational Biology & Bioinformatics pp 133-139 | Cite as
Exploring the High Performance Computing-Enablement of a Suite of Gene-Knockout Based Genetic Engineering Applications
Abstract
Genetic engineering provides methods to modify the genes of microorganisms to achieve desired effects. This can be done for improved organism growth rate or increasing production yield of a desired gene product. Gene knockout is a technique that can improve the specific characteristics of microorganisms by disabling selected sets of genes. However, microorganisms are complex and predicting the effects of gene modification is difficult. Several algorithms have been proposed to support a range of gene knockout strategies, including BAFBA, BHFBA and DBFBA. In this paper, scaling these algorithms and methods to utilise High Performance Computing (HPC) resources have been explored. The applications have been parallelized on HPC and the scalability and performance of these approaches were explored and documented.
Keywords
High performance computing HPC Gene knockout Genetic engineering Bees algorithm Flux balancePreview
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