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Philos Trans A Math Phys Eng Sci. 2015 Jul 28;373(2046). pii: 20140218. doi: 10.1098/rsta.2014.0218.

Bacterial computing with engineered populations.

Author information

1
School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, Manchester M1 5GD, UK m.amos@mmu.ac.uk.
2
Institut für Synthetische Mikrobiologie, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany.
3
Institut für Pathologie, Charite-Universitätsmedizin Berlin, Berlin, Germany.
4
Intergenomics Group, Instituto de Biomedicina y Biotecnología de Cantabria, Universidad de Cantabria, Cantabria, Spain.
5
School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK.
6
Laboratorio de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid 28040, Spain.
7
Systems Biophysics and Bionanotechnology, Technische Universität München, München, Germany.

Abstract

We describe strategies for the construction of bacterial computing platforms by describing a number of results from the recently completed bacterial computing with engineered populations project. In general, the implementation of such systems requires a framework containing various components such as intracellular circuits, single cell input/output and cell-cell interfacing, as well as extensive analysis. In this overview paper, we describe our approach to each of these, and suggest possible areas for future research.

KEYWORDS:

conjugation; mathematical modelling; simulation; synthetic biology; unconventional computing

PMID:
26078340
DOI:
10.1098/rsta.2014.0218
[Indexed for MEDLINE]
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