Scientific Reports (Jul 2023)

BMX: Biological modelling and interface exchange

  • Bruce J. Palmer,
  • Ann S. Almgren,
  • Connah G. M. Johnson,
  • Andrew T. Myers,
  • William R. Cannon

DOI
https://doi.org/10.1038/s41598-023-39150-1
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 10

Abstract

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Abstract High performance computing has a great potential to provide a range of significant benefits for investigating biological systems. These systems often present large modelling problems with many coupled subsystems, such as when studying colonies of bacteria cells. The aim to understand cell colonies has generated substantial interest as they can have strong economic and societal impacts through their roles in in industrial bioreactors and complex community structures, called biofilms, found in clinical settings. Investigating these communities through realistic models can rapidly exceed the capabilities of current serial software. Here, we introduce BMX, a software system developed for the high performance modelling of large cell communities by utilising GPU acceleration. BMX builds upon the AMRex adaptive mesh refinement package to efficiently model cell colony formation under realistic laboratory conditions. Using simple test scenarios with varying nutrient availability, we show that BMX is capable of correctly reproducing observed behavior of bacterial colonies on realistic time scales demonstrating a potential application of high performance computing to colony modelling. The open source software is available from the zenodo repository https://doi.org/10.5281/zenodo.8084270 under the BSD-2-Clause licence.