Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Virtual Spectroscopy for Fun and Profit

Bio/Technology volume 13, pages 236–238 (1995)Cite this article

Abstract

A physicomathematical approach to decoding the relationship between amino acid sequence and protein function may provide a novel way of designing biologically active peptides

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

References

  1. Kanochisa, M. 1988. A multivariant analysis method for discriminating protein secondary structural segments. Protein Engineering 2: 87–92.

    Article  Google Scholar 

  2. Nakai, K., Kidera, A., and Kanechisa, M. 1988. Cluster analysis of amino acid indices for prediction of protein structure and function. Protein Engineering 2: 93–100.

    Article  CAS  Google Scholar 

  3. Cosic, I. 1994. Macromolecular bioactivity: Is it resonant interaction between macromolecules?-Theory and applications. IEEE Transactions on Biomedical Engineering 41 12: 1101–1114.

    Article  Google Scholar 

  4. Cosic, I.M., and Vojisavljevic, V. 1989. Prediction of “hot spots” in interleukin-2. based on informational spectrum, characteristics of growth regulating factors. Biochimie 3: 333–342.

    Article  Google Scholar 

  5. Cosic I. and Hearn, M.T. 1991. “Hot spot” amino acid distribution in Ha-ras oncogene product p21: relationship to guanine binding site. J. Molecular Recognition 4: 57–62.

    Article  CAS  Google Scholar 

  6. Cosic, I. and Nesic, D. 1988. Prediction of “hot spots” in SV40 enhancer and relation with experimental data. Eur. J. Biochem. 170: 247–252.

    Article  Google Scholar 

  7. Cosic, I., Drummond, A.E., Underwood, J.R. and Hearn, M.T.W. 1994. A new approach to growth factor analogue design: modelling of FGF analogues. Molecular and Cellular Biochem. 130: 1–9.

    Article  CAS  Google Scholar 

  8. Krsmanovic, V., Cosic, I., Biquard, J.M., and Hearn, M.T.V. 1993. Artificial peptides and induced antibodies. Patent number WO93/17108.

Download references

Author information

Authors and Affiliations

  1. at the department of electrical and computer systems engineering, Monash University, Caulfield, Victoria, 3145, Australia

    Irena Cosic

Authors
  1. Irena Cosic
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cosic, I. Virtual Spectroscopy for Fun and Profit. Nat Biotechnol 13, 236–238 (1995). https://doi.org/10.1038/nbt0395-236

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nbt0395-236

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing