Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Understanding Science Through the Computational Lens

  • Published:
Journal of Computer Science and Technology Aims and scope Submit manuscript

Abstract

This article explores the changing nature of the interaction between computer science and the natural and social sciences. After briefly tracing the history of scientific computation, the article presents the concept of computational lens, a metaphor for a new relationship that is emerging between the world of computation and the world of the sciences. Our main thesis is that, in many scientific fields, the processes being studied can be viewed as computational in nature, in the sense that the processes perform dynamic transformations on information represented as digital data. Viewing natural or engineered systems through the lens of their computational requirements or capabilities provides new insights and ways of thinking. A number of examples are discussed in support of this thesis. The examples are from various fields, including quantum computing, statistical physics, the World Wide Web and the Internet, mathematics, and computational molecular biology.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Sloan Digital Sky Survey. http://www.sdss.org/.

  2. The Group of Theory at Berkeley Website. http://theo-ry.cs.berkeley.edu/.

  3. Papadimitriou C H. The algorithmic lens: How the computational perspective is transforming the sciences. In 2007 Federated Computing Research Conference, Speech, San Diego, USA, Jun. 8–16, 2007.

  4. Papadimitriou C H. Algorithms, Games, and the Internet. In Proc. STOC/ICALP 2001, Heraklion, Greece, July 6–8, 2001, pp.749-753.

  5. van Dam W, Mosca M, Vazirani U. How powerful is adiabatic quantum computation. In Proc. Symposium on the Foundation of Computer Science, Las Vegas, USA, Oct. 14–17, 2001, p.279.

  6. Mossel E, Peres Y, Sinclair A. Shuffling by semi-random transpositions. Mathematics arXiv math.PR/0404438, April 2004, Conference version appeared in Proc. IEEE FOCS 2004, Rome, Italy, Oct. 17–19, pp.572-581.

  7. Xing E P, Karp R M. MotifPrototyper: A Bayesian profile model for motif families. Proc. Nat. Acad. Sci., USA, Jul. 20, 2004, 101(29): 10523–10528.

    Article  Google Scholar 

  8. Ben-Dor A, Chor B, Karp R, Yakhini Z. Discovering local structure in gene expression data: The order preserving submatrix problem. Journal of Computational Biology, 2003, 10(3/4): 373–384.

    Article  Google Scholar 

  9. Aaronson S. The Limits of Quantum Computers. http://www.scottaaronson.com/talks/sipbtalk.ppt.

  10. Albert Einstein. Letter to Max Born (4 December 1926). The Born-Einstein Letters, translated by Irene Born, New York: Walker and Company, 1971, ISBN 0-8027-0326-7. This quote is commonly paraphrased “God does not play dice” or “God does not play dice with the universe”, and other slight variants.

  11. Shor P. Algorithms for quantum computation: Discrete logarithms and factoring. In Proc. the 35th Annual Symposium on Foundations of Computer Science, Los Alamitos, USA, Nov. 20–22, 1994, pp.124-134.

  12. Jerrum M, Sinclair A, Vigoda E. A polynomial-time approximation algorithm for the permanent of a matrix with nonnegative entries. Journal of the ACM, 2004, 51(4): 671–697.

    Article  MATH  MathSciNet  Google Scholar 

  13. Braunstein A, Mézard M, Zecchina R. Survey propagation: An algorithm for satisfiability. Random structures & Algorithms, 2005, 27(2): 201–226.

    Article  MATH  MathSciNet  Google Scholar 

  14. Etessami K, Yannakakis M. On the complexity of Nash equilibria and other fixed points. In Proc. the 48th IEEE Symp. Foundations of Computer Science (FOCS), Providence, USA, Oct. 20–23, 2007, pp.113-123.

  15. Nisan N, Roughgarden T, Tardos E, Vazirani V V (eds.). Algorithmic Game Theory. Cambridge University Press, 2007.

  16. Cipra B A. Some assembly required. SIAM News. Dec. 1, 2003, 36(10).

  17. Davidson E H. Genomic Regulatory Systems: Development and Evolution. Academic Press, 2001.

  18. Patrik D’haeseleer. What are DNA sequence motifs? Nature Biotechnology, 2006, 24: 423–425.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, 94720-1776, U.S.A

    Richard M. Karp

Authors
  1. Richard M. Karp
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Richard M. Karp.

Additional information

This work is supported in part by the National Science Foundation of USA for SGER under Grant No. CCF-0652536 “Planning for a Cross-Cutting Initiative in Computational Discovery” and Einstein Professorship of Chinese Academy of Sciences.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Karp, R.M. Understanding Science Through the Computational Lens. J. Comput. Sci. Technol. 26, 569–577 (2011). https://doi.org/10.1007/s11390-011-1157-0

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11390-011-1157-0

Keywords

Search

Navigation