Skip to main content
  • 137 Accesses

Abstract

It may be stretching credulity a little to suggest that cells think! But they do talk, in a sense. They, and a myriad biochemical agents within them, ‘talk’ to each other. Quite unlike the silent servants of an autocratic executive power we have come to expect, they chatter ceaselessly to organise themselves. And they do so, not as a token of resistance, but because by such means they ‘know’ best what is needed.

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 EPUB and 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
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover 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.

Notes

  1. Shankaran H, Resat, H. and Wiley, H.S. (2007) ‘Cell surface receptors for signal transduction and ligand transport — a design principles study’, PLoS: Computational Biology, 3, e101.

    Article  Google Scholar 

  2. Cselenyi, C.S. and Lee, E. (2008) ‘Context-dependent activation or inhibition of Wnt-β-Catenin signaling’, Science Signaling, 1, 10.

    Article  Google Scholar 

  3. Wiley H.S., Shvartsman, S.Y. and Lauffenburger, D.A. (2003) ‘Computational modeling of the EGF-receptor system: A paradigm for systems biology’, Trends in Cell Biology, 13, 1–43.

    Article  Google Scholar 

  4. Hlavacek, W.S. and Faeder, J.R. (2009) ‘The complexity of cell signaling and the need for a new mechanic’, Science Signaling, 2, e46.

    Article  Google Scholar 

  5. Ray, L.B. and Gough, N.R. (2002) ‘Orienteering strategies for a signaling maze’, Science, 296, 1632–33.

    Article  Google Scholar 

  6. Golub, T., Wacah, S. and Caroni, P. (2003) ‘Spatial and temporal control of signaling through lipid rafts’, Current Opinion in Neurobiology, 14, 542–50.

    Article  Google Scholar 

  7. Sachs, K., Perez, O., Pe’er, D., Lauffenburger, D.A. and Nolan, G.P. (2005) ‘Causal protein-signaling networks derived from multiparameter single-cell data’, Science, 308, 523–6.

    Article  Google Scholar 

  8. Kashtan, N. and Alon, U. (2005) ‘Spontaneous evolution of modularity and network motifs’, Proceedings of the National Acacdemy of Sciences, 102, 13773–8.

    Article  Google Scholar 

  9. Wagner, G.P., Pavlicev, M. and Cheverud, J.M. (2007) ‘The road to modularity’, Nature Reviews: Genetics, 8, 921–6.

    Article  Google Scholar 

  10. López-Maury, L. Marguerat, S and Bähler, J. (2008) ‘Tuning gene expression to changing environments’, Nature Reviews: Genetics, 9, 583–94.

    Article  Google Scholar 

  11. Pearson, H. (2008) ‘The cellular hullabaloo’, Nature, 453, p. 150.

    Article  Google Scholar 

  12. Schadt, E.E., Sachs, A. and Friend, S. (2005) ‘Embracing complexity, inching closer to reality’, Science STKE, 295, e40.

    Google Scholar 

  13. Vaudry, D., Stork, P.J.S., Lazarovici, P. and Elden, L.E. (2002) ‘Signaling pathways for C12 differentiation: Making the right connections’, Science, 296, 1646–7.

    Article  Google Scholar 

  14. Natarajan, M., Lin, K-M., Hsueh, R.C., Sternweis, P.C. and Ranganathan, R. (2006) ‘A global analysis of cross-talk in a mammalian cellular signalling network’, Nature Cell Biology, 8, p. 571.

    Article  Google Scholar 

  15. Shvartsman, S.Y., Wiley, H.S. and Lauffenburger, D.A. (2004) ‘Spatiotemporal dynamics of autocrine loops in the epidermal growth factor receptor system’, IEEE Control Systems Magazine, 53–62.

    Google Scholar 

  16. Rosenbaum, D.M., Rasmussen, S.G.F. and Kobilka, B.K. (2009) ‘The structure and function of G-protein-coupled receptors’, Nature, 459, 356–63.

    Article  Google Scholar 

  17. Flaherty, P., Radhakrishnan, M.L., Dinh, T., Rebres, R.A., Roach, T.I., et al. (2008) ‘A dual receptor crosstalk model of G-protein-coupled signal transduction’, PLoS Computional Biology, 4, e1000185.

    Google Scholar 

  18. Bromley, S.K., Mempel, T.R. and Luster, A.R. (2008) ‘Orchestrating the orchestrators: Chemokines in control of T cell traffic’, Nature Immunology, 9, 970–80.

    Article  Google Scholar 

  19. Singleton, K.L., Roybal, K.Y., Sun, Y., Fu, G., Gascoigne, N.R.J., van Oers, N.S.C. and Wülfing, C. (2009) ‘Spatiotemporal patterning during T cell activation is highly diverse’, Science Signaling, 2, ra15.

    Article  Google Scholar 

  20. Bestebroer J., van Kessel, K.P.M., Azouagh, H., Walenkamp, A.M., Boer, I.G.J., Romijn, R.A., van Strijp, J.A.G. and de Haas, C.J.C. (2009) ‘Staphylococcal SSL5 inhibits leukocyte activation by chemokines and anaphylatoxins’, Blood, 113, 328–37.

    Article  Google Scholar 

  21. Chalfie, M. (2009) ‘Neurosensory mechanotransduction’, Nature Reviews: Molecular Cell Biology, 10, 44–9.

    Article  Google Scholar 

  22. Wang, N., Tytell, J.D. and Ingber, D.E. (2009) ‘Mechanotransduction at a distance: Mechanically coupling the extracellular matrix with the nucleus’, Nature Reviews: Molecular Cell Biology, 10, 75–81.

    Article  Google Scholar 

  23. Geiger, B., Spatz, J.P. and Bershadsky, A.D. (2009) ‘Environmental sensing through focal adhesions’, Nature Reviews: Molecular Cell Biology, 10, 21–30.

    Article  Google Scholar 

  24. Ma, X.M. and Blenis, L. (2009) ‘Molecular mechanisms of mTOR-mediated translational control’, Molecular Cell Biology, 10, 307.

    Google Scholar 

  25. Gilbert, W. (1978) ‘Why genes in pieces?’ Nature, 271, 501.

    Article  Google Scholar 

  26. Le Hir, H., Nott, A. and Moore, M.J. (2003) ‘How introns influence and enhance eukaryotic gene expression’, Trends in Biochemical Sciences, 28, 215–20.

    Article  Google Scholar 

  27. Johnson, J.M., Castle, J., Garrett-Engele, P., Kan, Z., Loerch, P.M., Armour, C.D., Santos, R., Schadt, E.E., Stoughton, R. and Shoemaker, D.D. (2003) ‘Genome-wide survey of human alternative pre-mRNA splicing with exon junction microarrays’, Science, 302, 2141–4.

    Article  Google Scholar 

  28. Liu, M. and Grigoriev, A. (2004) ‘Genome analysis protein domains correlate strongly with exons in multiple eukaryotic genomes — evidence of exon shuffling?’, Trends in Genetics, 20, 399–405.

    Article  Google Scholar 

  29. Saxonov, S. and Gilbert, W. (2003) ‘The universe of exons revisited’, Genetica, 118, 167–278.

    Article  Google Scholar 

  30. Mattick, J.S. (2003) ‘Challenging the dogma: The hidden layer of nonprotein-coding RNAs in complex organisms’, BioEssays, 25, 930–939.

    Article  Google Scholar 

  31. Storz, G. (2002) ‘An expanding universe of noncoding RNAs’, Science 296, 1260–3.

    Article  Google Scholar 

  32. Valadkhan S. and Nilsen T.W. (2010) ‘Reprogramming of the noncoding transcriptome during brain development’, Journal of Biology, 9, 5.

    Article  Google Scholar 

  33. Gannon, F. and Pariente, N. (2008) ‘Variations on complexity’, EMBO Reports, 9, 6, 493.

    Article  Google Scholar 

  34. Bar-Yam, Y., Harmon, D. and de Bivort, B. (2009) ‘Attractors and democratic dynamics’, Science, 323, 1016–17.

    Article  Google Scholar 

  35. Levine, M. and Tjian, R. (2003) ‘Transcription regulation and animal diversity’, Nature, 424, 147–51.

    Article  Google Scholar 

  36. Durand, D. (2003) ‘Vertebrate evolution: Doubling and shuffling with a full deck’, Trends in Genetics, 19, 2–5.

    Article  Google Scholar 

  37. Nykter, M., Price, N.D., Aldana, M., Ramsey, S.A., Kauffman, S.A., Leroy E. Hood, L.E., Yli-Harja, O. and Shmulevich, I. (2008) ‘Gene expression dynamics in the macrophage exhibit criticality’, PNAS, 105, 1897–900.

    Article  Google Scholar 

  38. Wuensche, A. (2002) ‘Basins of attraction in network dynamics: A conceptual framework for biomolecular networks’, Santa Fe Instititute Working Paper, 02, 02–004.

    Google Scholar 

  39. Shankaran, H. and Wiley, H.S. (2008) ‘Smad signaling dynamics: Insights from a parsimonious model’, Science Signaling, 36, e41.

    Google Scholar 

  40. Sole, R.V., Cancho, R.F., Montoya, J.M. and Valverde, S. (2002) ‘Selection, tinkering and emergence in complex networks’, Santa Fe Working Papers, 02, 07–029.

    Google Scholar 

  41. Luscombe, N.M., Babu, M.M., Yu, H., Snyder, M. and Teichmann, S.A. (2004) ‘Genomic analysis of regulatory network dynamics reveals large topological changes’, Nature, 431, 308–12.

    Article  Google Scholar 

  42. Morowitz, H.J., Kosgelnik, J.D., Yang, J. and Coey, G. (2000) ‘The origin of intermediary metabolism’, Proceedings of the National Academy of Sciences, 97, 7704–8.

    Article  Google Scholar 

  43. Rose, S. (1997) Lifelines, London: Penguin. p. 17.

    Google Scholar 

  44. Nederbragt, H. (1997) ‘Hierarchical organisation of biological systems and the structure of adaptation in evolution and tumorigenesis’, Journal of Theoretical Biology, 184, p. 151.

    Article  Google Scholar 

  45. Glass, L. (1991) ‘Nonlinear dynamics of physiological function and control’, 1, 247–50.

    Google Scholar 

  46. Shelhamer, M. (2008) Nonlinear Dynamics in Physiology: A State-Space Approach, New York: World Scientific.

    Google Scholar 

  47. Krain, L.P. and Denver, R.J. (2004) ‘Developmental expression and hormonal regulation of glucocorticoid and thyroid hormone receptors during metamorphosis in Xenopus laevis’, Journal of Endocrinology, 181, p. 102.

    Article  Google Scholar 

  48. Yates, F.E. (2008) ‘Homeokinetics/homeodynamics: A physical heuristic for life and complexity’, Ecological Psychology, 20, 148–79.

    Article  Google Scholar 

  49. Joels, M. and Baram, T.Z. (2009) ‘The neuro-symphony of stress’, Nature Reviews: Neuroscience, 10, 459–66.

    Google Scholar 

  50. Shelhamer, M. (2006) Nonlinear Dynamics in Physiology: A State-Space Approach, New York: World Scientific.

    Book  Google Scholar 

  51. Goldberger, A.L., Amaral, L.A.N., Hausdorff, J.M., Ivanov, P. Ch., Peng, C-K. and Stanley, H.E. (2002) ‘Fractal dynamics in physiology: Alterations with disease and aging’, Proceedings of the National Academy of Sciences, 99, 1, 2466–72.

    Article  Google Scholar 

  52. Costa, M, Goldberger, A.L. and Peng, C-K. (2002) ‘Multiscale entropy analysis of complex physiologic time series’, Physical Review Letters, 89, 1–4.

    Article  Google Scholar 

  53. Sabelli, H. and Abouzeid, A. (2002) ‘Definition and empirical characterization of creative processes’, Nonlinear Dynamics, Psychology and Life Sciences, 7, 35–47.

    Article  Google Scholar 

Download references

Authors

Copyright information

© 2010 Ken Richardson

About this chapter

Cite this chapter

Richardson, K. (2010). Bodily Intelligence. In: The Evolution of Intelligent Systems. Palgrave Macmillan, London. https://doi.org/10.1057/9780230299245_4

Download citation

Publish with us

Policies and ethics