Owen Gilfellon

PhD Student

2nd year PhD student, studying Computer Intelligence applied to the engineering of Bacillus subtilis, in association with Microsoft Research, Cambridge.

Current Synthetic Biology designs are generally small scale and produced manually, using large amounts of specific domain knowledge. The development of automated computational tools that utilise Computer Intelligence has the potential to extend the scale of possible designs, providing the framework for genome-scale engineering.

Work on the automated design of simple devices will be the basis for research into the full or partial automation of the full Synthetic Biology process. Important to this will be investigating how to best abstract the complexity of the underlying biology.

Research Interests

  • Synthetic Biology
  • Networks
  • Complex Systems
  • Computer Intelligence
    • Artificial Neural Networks
    • Evolutionary Algorithms


  • J. Hallinan, O. Gilfellon, G. Misirli, and A. Wipat, “Tuning receiver characteristics in bacterial quorum communication: an evolutionary approach using standard virtual biological parts,” in Computational intelligence in bioinformatics and computational biology, 2014 ieee conference on, 2014, pp. 1-8.
    title={Tuning receiver characteristics in bacterial quorum communication: An evolutionary approach using standard virtual biological parts},
    author={Hallinan, JS and Gilfellon, O and Misirli, G and Wipat, A},
    booktitle={Computational Intelligence in Bioinformatics and Computational Biology, 2014 IEEE Conference on},



Address: Room 924, School of Computing Science, Claremont Tower, Newcastle University, Newcastle upon Tyne, NE1 7RU

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