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Collaborative Multidiscipline/Multiscale Analysis, Modeling, Simulation and Integration in Complex Systems: System Biology

  • Thomas J. Wheeler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3980)

Abstract

Analysis, Modeling and Integration of Complex Systems are difficult. Collaboration among dissimilar disciplines is difficult. But, integrated interdisciplinary collaboration is essential in making sense of complex systems. This creates a dilemma with complex systems at the end of one horn and interdisciplinary collaboration at the other. There is another wrinkle, combining the conceptual spaces at the ends of the horns makes each much more difficult.

Rather than trying to pass between the horns of this dilemma, we weave a semantic unification space between them. This does more than ironing out the wrinkle; the threads of common image schemas, cognitive metaphors and conceptual interfaces form a mesh between the organizations of each problem, making the combined problem easier that either is separately. This paper presents a naturally valid, both discipline specific and discipline integrating, framework and a new foundationsl semantic mechanism for making multidisciplinary sense of complex systems

Keywords

System Biology Image Schema Interdisciplinary Collaboration Open Arrow Conceptual Metaphor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Johnson, M.: The Body In The Mind: Bodily Basis Of Meaning, Imagination, And Reason. University of Chicago press (1987)Google Scholar
  2. Lakoff, G., Johnson, M.: Philosophy In: The Flesh-The Embodied Mind And Its Challenge To Western Thought. Basic Books, New YorkGoogle Scholar
  3. Gibson, J.: Ecological Visual Perception. Lawrencee Erlbaum Associates, Hillsdale (1986)Google Scholar
  4. Land, E.: The Retinex Theory Of Colour Vision. Proc. R. Instn. G. B. 47, 23–58 (1974)Google Scholar
  5. Zeki, S.: A Vision Of The Brain. Blackwell Scientific Publications, Malden (1993)Google Scholar
  6. Mandler, J.M.: The Foundations of Mind: Origins of Conceptual Thought. Oxford University Press, Oxford (2004)Google Scholar
  7. Lakoff, G., Johnson, M.: Metaphors We Live By. University Of Chicago Press, Chicago (1980)Google Scholar
  8. Fauconnier, G., Turner, M.: The Way We Think: Conceptual Blending And The Mind’s Hidden Complexities. Basic Books, New York (2002)Google Scholar
  9. Collins, J.: Integrating synthetic biology and systems biology ICSB 2005 (2005)Google Scholar
  10. Harel, D.: Comprehensive and realistic modeling of biological systems: what, how and why ICSB 2005 (2005)Google Scholar
  11. Paton, N., et al.: Conceptual modelling of genomic information bioinformatics  16(6) (2000)Google Scholar
  12. Bult, C.: Curated Ontologies and Semantic Integration. In: BIBE 2000 (2000)Google Scholar
  13. Hill, D.: An Introduction to the Gene Ontology. In: GORECOMB 2005, Cambridge MA (2005)Google Scholar
  14. Wheeler, T., Dolan, M.: Support for Interdisciplinary Conceptual Model Blending. In: Intl. Conf. Intelligent User interfaces (October 2001)Google Scholar
  15. Philippi, S., Kohler, J.: Using XML technology for the ontology-based semantic integration of life science databases. IEEE Trans. Inf. Technol. Biomed. 8(2) (June 2004)Google Scholar
  16. Davidson, S.: Bioklesli: A Digital Library For Biomedical Research. Intl. J. Digit. Lib. 1 (January 1997)Google Scholar
  17. Wiederhold, G.: Mediators In The Architecture Of Future Information Systems. Published In IEEE Computer (March 1992); Bloom, M., Peterson, M., Nadel, L., Garrett, M.: language and space. Mit press, Cambridge (1996)Google Scholar
  18. Frank, A.U., Mark, D.M. (eds.): Cognitive and Linguistic Aspects of Geographic Space. NATO ASI Series D, vol. 63. Kluwer Academic Publishers, Dordrecht (1991)Google Scholar
  19. Frank, A.U., Mark, D.M. (eds.): Cognitive and Linguistic Aspects of Geographic Space. NATO ASI Series D, vol. 63. Kluwer Academic Publishers, Dordrecht (1991)Google Scholar
  20. Worboys, M.F., Duckham, M.: GIS: A Computing Perspective, 2nd edn. CRC Press, Boca Raton (2004) ISBN: 0415283752Google Scholar
  21. Leibe, B., Schiele, B.: Analyzing Appearance and Contour Based Methods for Object Categorization. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2003), Madison, USA (June 2003)Google Scholar
  22. Espinosa, J.A., Kraut, R.E., Slaughter, S.A., Lerch, J.F., Herbsleb, J.D., Mockus, A.: Shared Mental Models, familiarity, and coordination: A multi-method study of distributed software teams. In: International Conference in Information Systems, Barcelona, Spain (2002)Google Scholar
  23. Jensen, J.H., Gordon, M.S.: J. Chem. Phys. 108, 4772 (1998)CrossRefGoogle Scholar
  24. Jensen, J.H.: J. Chem. Phys. 114, 220 (2001)CrossRefGoogle Scholar
  25. Bailey, D., Feldman, J., Narayanan, S., Lakoff, G.: Modeling embodied lexical development. In: Proceedings of the 19th Cognitive Science Society Conference (1997)Google Scholar
  26. Suchman, L.: Plans and Situated actions. Cambridge University Press, Cambridge (1987)Google Scholar
  27. Norman, D.: The Design Of Everyday Things. Penguin (1986)Google Scholar
  28. Piaget, J.: Structuralism Harper (1970)Google Scholar
  29. Bar-yam, Y.: A Mathematically Theory of Strong Emergence. Complexity 8(6) (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Thomas J. Wheeler
    • 1
  1. 1.Computer Science DeptUniversity of Maine 

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