Computing with bacterial constituents, cells and populations: from bioputing to bactoputing

Vic Norris; Abdallah Zemirline; Patrick Amar; Jean Nicolas Audinot; Pascal Ballet; Eshel Ben-Jacob; Gilles Bernot; Guillaume Beslon; Armelle Cabin; Eric Fanchon; Jean-Louis Giavitto; Nicolas Glade; Patrick Greussay; Yohann Grondin; James A Foster; Guillaume Hutzler; Jürgen Jost; Francois Kepes; Olivier Michel; Franck Molina; Jacqueline Signorini; Pasquale Stano; Alain R Thierry

Computing with bacterial constituents, cells and populations: from bioputing to bactoputing

Vic Norris ¹ Abdallah Zemirline ² Patrick Amar ^{3, 4} Jean Nicolas Audinot ⁵ Pascal Ballet ^{6, 7} Eshel Ben-Jacob ⁸ Gilles Bernot ⁹ Guillaume Beslon ^{10, 11} Armelle Cabin ¹ Eric Fanchon ¹² Jean-Louis Giavitto ^{13, 14} Nicolas Glade ¹⁵ Patrick Greussay ¹⁶ Yohann Grondin ¹⁷ James A Foster ¹⁸ Guillaume Hutzler ¹⁹ Jürgen Jost ^{20, 21} Francois Kepes ²² Olivier Michel ²³ Franck Molina ²⁴ Jacqueline Signorini ²⁵ Pasquale Stano ²⁶ Alain R Thierry ²⁴

1 AMMIS - Assemblages moléculaires : modélisation et imagerie SIMS

2 LISYC - Laboratoire d'Informatique des Systèmes Complexes

3 LRI - Laboratoire de Recherche en Informatique

4 AMIB - Algorithms and Models for Integrative Biology

LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France

5 Département Science et Analyse des Matériaux - SAM (Belvaux, Luxembourg)

6 Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance

7 UBO - Université de Brest

8 School of Physics and Astronomy [Tel Aviv]

9 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe BIOINFO

Laboratoire I3S - MDSC - Modèles Discrets pour les Systèmes Complexes

10 LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information

11 BEAGLE - Artificial Evolution and Computational Biology

LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558, Inria Grenoble - Rhône-Alpes, LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information

12 TIMC-IMAG-BCM - Biologie Computationnelle et Mathématique

TIMC-IMAG - Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble - UMR 5525

13 IRCAM - Institut de Recherche et Coordination Acoustique/Musique

14 MuTant - Synchronous Realtime Processing and Programming of Music Signals

Inria Paris-Rocquencourt, UPMC - Université Pierre et Marie Curie - Paris 6, IRCAM, CNRS - Centre National de la Recherche Scientifique

15 AGIM - AGeing and IMagery

16 LIASD - Laboratoire d'Informatique Avancée de Saint-Denis

17 Department of Physics and Astronomy [Leicester]

18 Department of Biological Sciences [Idaho]

19 COSMO

IBISC - Informatique, Biologie Intégrative et Systèmes Complexes

20 MPI-MiS - Max Planck Institute for Mathematics in the Sciences

21 Santa Fe Institute

22 Génopole [Evry]

23 LACL - Laboratoire d'Algorithmique Complexité et Logique

24 SysDiag - Sysdiag-Modélisation et Ingénierie des Systèmes Complexes Biologiques pour le Diagnostic

25 Laboratoire d'Intelligence Artificielle [Saint-Denis]

26 Enrico Fermi - Dipartimento di Fisica

Abstract : The relevance of biological materials and processes to computing-alias bioputing-has been explored for decades. These materials include DNA, RNA and proteins, while the processes include transcription, translation, signal transduction and regulation. Recently, the use of bacteria themselves as living computers has been explored but this use generally falls within the classical paradigm of computing. Computer scientists, however, have a variety of problems to which they seek solutions, while microbiologists are having new insights into the problems bacteria are solving and how they are solving them. Here, we envisage that bacteria might be used for new sorts of computing. These could be based on the capacity of bacteria to grow, move and adapt to a myriad different fickle environments both as individuals and as populations of bacteria plus bacteriophage. New principles might be based on the way that bacteria explore phenotype space via hyperstructure dynamics and the fundamental nature of the cell cycle. This computing might even extend to developing a high level language appropriate to using populations of bacteria and bacteriophage. Here, we offer a speculative tour of what we term bactoputing, namely the use of the natural behaviour of bacteria for calculating.

Document type :

Journal articles

Domain :

Computer Science [cs] / Bioinformatics [q-bio.QM]

Life Sciences [q-bio] / Quantitative Methods [q-bio.QM]

Complete list of metadatas

https://hal.inria.fr/hal-00643738
Contributor : Patrick Amar <>
Submitted on : Tuesday, November 22, 2011 - 4:42:04 PM
Last modification on : Monday, June 17, 2019 - 3:00:04 PM

Computing with bacterial constituents, cells and populations: from bioputing to bactoputing

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Computing with bacterial constituents, cells and populations: from bioputing to bactoputing

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