Skip to main content
Log in

The challenges of in silico biology

  • Feature
  • Published:

From Nature Biotechnology

View current issue Submit your manuscript

Moving from a reductionist paradigm to one that views cells as systems will necessitate changes in both the culture and the practice of research.

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

Access this article

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

Instant access to the full article PDF.

Figure 1: The shift in emphasis of biological research.
Figure 2: Constraining possible behaviors.
Figure 3: Narrowing down the alternatives.
Figure 4

References

  1. Eisenberg, D., Marcotte, E.M., Xenarios, I. & Yates, T.O. Protein function in the post-genomic era. Nature 405 , 823–826 (2000).

    Article  CAS  Google Scholar 

  2. Palsson, B.O. What lies beyond bioinformatics? Nat. Biotechnol. 15 , 3–4 (1997).

    Article  CAS  Google Scholar 

  3. Strothman, R.C. The coming Kuhnian revolution in biology. Nat. Biotechnol. 15, 194–199 (1997).

    Article  Google Scholar 

  4. Hartwell, L.H., Leibler, S. & Murray, A.W. From molecular to modular cell biology . Nature 402, C47–C52 (1999).

    Article  CAS  Google Scholar 

  5. Evans, G.A. Designer science and the “omic” revolution. Nat. Biotechnol. 18, 127 (2000).

    Article  CAS  Google Scholar 

  6. Bailey, J.E. Lessons from metabolic engineering for functional genomics and drug discovery . Nat. Biotechnol. 17, 616– 618 (1999).

    Article  CAS  Google Scholar 

  7. Aebersold, R., Hood, L.E., & Watts, J.D. Equipping scientists for the new biology. Nat. Biotechnol. 18, 359 (2000 ).

    Article  CAS  Google Scholar 

  8. McAdams, H.H. & Arkin, A. Simulation of prokaryotic genetic circuits. Annu. Rev. Biophys. Biomol. Struct. 27, 199–224 (1998).

    Article  CAS  Google Scholar 

  9. Lee, I.-D. & Palsson, B.O. A comprehensive model of human erythrocyte metabolism: extensions to include pH effects. Biomed. Biochim. Acta 49, 771–789 (1991).

    Google Scholar 

  10. McAdams, H.H. & Shapiro, L. Circuit simulation of genetic networks. Science 269, 651– 656 (1995).

    Article  Google Scholar 

  11. Schilling, C.H. et al. Metabolic pathway analysis: basic concepts and scientific applications in the post-genomic era. Biotechnol. Prog. 15, 296–303 (1999).

    Article  CAS  Google Scholar 

  12. Varma, A. & Palsson, B.O. Metabolic flux balancing: basic concepts, scientific and practical use. Bio/Technology 12, 994–998 (1994).

    Article  CAS  Google Scholar 

  13. Bonarius, H.P.J., Schmid, G. & Tramper, J. Flux analysis of underdetermined metabolic networks: the quest for the missing constraints. Trends Biotechnol. 15, 308–314 ( 1997).

    Article  CAS  Google Scholar 

  14. Reich, J.G. & Sel'kov, E.E. Energy metabolism of the cell Edn. 2. (Academic Press, New York, NY; 1981).

    Google Scholar 

  15. Heinrich, R. & Schuster, S. The regulation of cellular systems. (Chapman & Hall, New York, 1996 ), p.372.

    Book  Google Scholar 

  16. Fell, D. Understanding the control of metabolism. (Portland Press, London, UK; 1996).

    Google Scholar 

  17. Alter, O., Brown, P.O., & Botstein, D. Singular value decomposition for genome-wide expression data processing and modeling. PNAS 97, 10101 –10106 (2000).

    Article  CAS  Google Scholar 

  18. Holter, N.S., Mitra, M., Martian, A., Cieplak, M., Banavar, J.R. & Fedoroff, N.V. Fundamental patterns underlying gene expression profiles. PNAS 97, 8409–8414 ( 2000).

    Article  CAS  Google Scholar 

  19. Palsson, B.O. Joshi, A., & Ozturk, S. Reducing complexity in metabolic networks. Fed. Proc. 46, 2485–2489 (1987).

    CAS  PubMed  Google Scholar 

  20. Alon, U., Surette, M.G., Barkai, N. & Leibler, S. Robustness in bacterial chemotaxis. Nature 397, 168–171 (1999).

    Article  CAS  Google Scholar 

  21. von Dassow, G., Meir, E., Munro, E.M., & Odell, G.M. The segment polarity network is a robust developmental module. Nature 406, 188–192 ( 2000).

    Article  CAS  Google Scholar 

  22. Tomita, M. et al. E-CELL: software environment for whole-cell simulation. Bioinformatics 15, 72–84 ( 1999).

    Article  CAS  Google Scholar 

  23. Schilling, C.H., Edwards, J.S. & Palsson, B.O. Toward metabolic phenomics: analysis of genomic data using flux balances. Biotechnol. Prog. 15, 288–295 (1999).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

I thank Markus Covert, Jeremy Edwards, David Letscher and Christophe Schilling for preparing the figures.

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Palsson, B. The challenges of in silico biology. Nat Biotechnol 18, 1147–1150 (2000). https://doi.org/10.1038/81125

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/81125

  • Springer Nature America, Inc.

This article is cited by

Navigation