Skip to main content

Information Processing in Computational Tissues

  • Chapter
Book cover Information Processing in Cells and Tissues

Abstract

Biocomputation involves studying organisms using the metaphor of computers so we can discover both new ways of performing computation and defining living systems. An appropriate point to start any discussion of biocomputation is by contrasting the distinct properties of computers and biological systems. Only then is it possible to consider the concept of computation and whether some of the activities of both systems lie within our definition. As computers are man-made their properties are easily described: computers process symbolic information; they solve mathematical problems by algorithms. Physically they are composed of large, regular arrays of interconnected switches so that their component parts can interact in strictly controlled ways. This arrangement, called structural programmability, [Con85], gives computers the capability of simulating one symbol processing machine on another. The primary way of performing this simulation is recursion and sequence.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. N. Arber, G. Zajicek, and I. Ariel. The streaming liver II: Hepatocyte life history. Liver, 8:80–87, 1988.

    PubMed  CAS  Google Scholar 

  2. Michael Conrad. On design principles for a molecular computer. Communications Of The ACM, 28(5):464–480, 1985.

    Article  Google Scholar 

  3. Michael Conrad. Molecular computing: The lock-key paradigm. IEEE Computer, 25(11):11–20, 1992.

    Article  Google Scholar 

  4. Nicola Dioguardi. The Liver, The Hepatone and Its Functioning. Universita degli Studi di Milano, 1995.

    Google Scholar 

  5. Manfred Eigen, W. Gardiner, P. Schuster, and R WinklerOswatitsch. The origin of genetic information. Scientific American, 244(4):78–94, 1981.

    Article  Google Scholar 

  6. Manfred Eigen. Self-organization of matter and evolution of biological macromolecules. Naturwissenschaften, 58:465–522, 1971.

    Article  PubMed  CAS  Google Scholar 

  7. Gail Raney Fleishaker. Autopoiesis - the status of its system logic. Biosystems, 22(1):37–49, 1988.

    Article  Google Scholar 

  8. George Kampis. Self-modifying Systems In Biology And Cognitive Science. Pergamon Press, 1991.

    Google Scholar 

  9. George Kampis. Life-like computing beyond the machine metaphor. In Ray C. Paton, editor, Computing With Biological Metaphors. Chapman And Hall, 1994.

    Google Scholar 

  10. Arthur Koestler. The Ghost In The Machine. Arkana/Penguin Books, 1967.

    Google Scholar 

  11. R. Levins. Complex systems. In C. H. Waddington, editor, Towards A Theoretical Biology, volume 3, pages 73–88. Edinburgh University Press, 1970.

    Google Scholar 

  12. Ray C. Paton, H. S. Nwana, M. J. R. Shave, and T. J. M. Bench-Capon. Computing at the tissue/organ level. In F. J. Varela and P. Bourgine, editors, Towards a Practice of Autonomous Systems, pages 411–420. MIT Press, 1992.

    Google Scholar 

  13. Ilya Prigogine and Isabelle Stengers. Order Out Of Chaos: Man’s New Dialogue With Nature. Flamingo, 1985.

    Google Scholar 

  14. Robert Rosen. Some relational cell models: The metabolism-repair systems. In Robert Rosen, editor, Foundations Of Mathematical Biology, volume 2, pages 217–253. Academic Press, New York, 1972.

    Google Scholar 

  15. Stanley N. Salthe. Development And Evolution: Complexity and change in biology. MIT Press, 1993.

    Google Scholar 

  16. W. Richard Stark. Artificial tissue models. In Ray C. Paton, editor, Computing With Biological Metaphors. Chapman And Hall, 1994.

    Google Scholar 

  17. Francisco J. Varela. Principle of biological autonomy. North Holland, 1979.

    Google Scholar 

  18. E. R. Weibel. The non-statistical nature of biological structure and its implications on sampling for stereology. In Lecture Notes in Biomathematics: Geometrical Probability and Biological Structures, volume 23. Springer Verlag, Berlin, 1977.

    Google Scholar 

  19. Norbert Wiener. Cybernetics: or control and communication in the animal and machine. MIT Press, 1953.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer Science+Business Media New York

About this chapter

Cite this chapter

Butler, M.H., Paton, R.C., Leng, P.H. (1998). Information Processing in Computational Tissues. In: Holcombe, M., Paton, R. (eds) Information Processing in Cells and Tissues. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5345-8_19

Download citation

  • DOI: https://doi.org/10.1007/978-1-4615-5345-8_19

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7438-1

  • Online ISBN: 978-1-4615-5345-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics