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Using qualitative uncertainty in protein topology prediction

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Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU 1995)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 946))

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Abstract

The prediction of protein structure is an important problem in molecular biology. It is also a difficult problem since the available data are incomplete and uncertain. This paper describes models for the prediction of a particular level of protein structure, known as the topology, which handle uncertainty in a qualitative fashion.

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References

  1. Clark, D. A., Shirazi, J., and Rawlings, C. J. 1992. Protein topology prediction through constraint-based search and the evaluation of topological folding rules Protein Engineering, 4:751–760.

    Google Scholar 

  2. D. Dubois and H. Prade 1991 Fuzzy sets in approximate reasoning, Part 1: inference with possibility distributions, Fuzzy sets and systems, 40:143–202.

    Google Scholar 

  3. Heckerman, D. E. 1990. An empirical comparison of three inference methods. In Uncertainty in Artificial Intelligence 4, (R. D. Shachter, T. S. Levitt, L. N. Kanal, and J. F. Lemmer, eds.), Elsevier, Amsterdam.

    Google Scholar 

  4. Heckerman, D. E., and Shwe, M. 1993. Diagnosis of multiple faults: a sensitivity analysis, Proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence, Washington D. C.

    Google Scholar 

  5. Henrion, M., Provan, G., del Favero, B., and Sanders, G. 1994. An experimental comparison of diagnostic performance using infinitesimal and numerical bayesian belief networks, Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence, Seattle.

    Google Scholar 

  6. Parsons, S. 1995. Softening constraints in constraint-based protein topology prediction, Proceedings of the 3rd International Conference on Intelligent Systems for Molecular Biology, Cambridge, UK.

    Google Scholar 

  7. Parsons, S. 1995. Hybrid models of uncertainty in protein topology prediction, Applied Artificial Intelligence, 9:335–351.

    Google Scholar 

  8. Parsons, S. 1993. Qualitative methods for reasoning under uncertainty, PhD Thesis, Queen Mary and Westfield College, London (to be published by MIT Press).

    Google Scholar 

  9. Parsons, S. and Saffiotti, A. 1993. Integrating uncertainty handling techniques in distributed artificial intelligence, in: Symbolic and Quantitative Approaches to Reasoning and Uncertainty, (M. Clarke, R, Kruse and S. Moral, eds.), Springer Verlag.

    Google Scholar 

  10. Saffiotti, A., Parsons, S. and Umkehrer, E. 1994. A case study in comparing uncertainty management techniques, Microcomputers in Civil Engineering — Special Issue on Uncertainty in Expert Systems, 9:367–380.

    Google Scholar 

  11. Shenoy, P. P. 1991. A valuation-based language for expert systems, International Journal of Approximate Reasoning, 3:383–411.

    Google Scholar 

  12. Shirazi, J., Clark, D. A. and Rawlings, C. J. 1990. Constraint-based reasoning in molecular biology: predicting protein topology from secondary structure and topological constraints, BCU/ICRF Technical Report.

    Google Scholar 

  13. Taylor, W. R. and Green, N. M. 1989. The predicted secondary structure of the nucleotide binding sites of six cation-transporting ATPases leads to a probable tertiary fold European Journal of Biochemistry, 179:241–248.

    PubMed  Google Scholar 

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Christine Froidevaux Jürg Kohlas

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© 1995 Springer-Verlag Berlin Heidelberg

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Parsons, S. (1995). Using qualitative uncertainty in protein topology prediction. In: Froidevaux, C., Kohlas, J. (eds) Symbolic and Quantitative Approaches to Reasoning and Uncertainty. ECSQARU 1995. Lecture Notes in Computer Science, vol 946. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60112-0_39

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  • DOI: https://doi.org/10.1007/3-540-60112-0_39

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60112-8

  • Online ISBN: 978-3-540-49438-6

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