Corpus ID: 174251

Softening Constraints in Constraint-Based Protein Topology Prediction

  title={Softening Constraints in Constraint-Based Protein Topology Prediction},
  author={S. Parsons},
  journal={Proceedings. International Conference on Intelligent Systems for Molecular Biology},
  • S. Parsons
  • Published 1995
  • Computer Science, Medicine
  • Proceedings. International Conference on Intelligent Systems for Molecular Biology
  • This paper is concerned with the handling of uncertain data about the applicability of constraints in protein topology prediction. It discusses the use of novel methods of representing and reasoning with uncertain data, and presents the results of some experiments in using these methods to build probabilistic models of constraint application. It thus builds on work by other authors in both constraint satisfaction and probabilistic reasoning. 
    2 Citations

    Figures, Tables, and Topics from this paper

    Using Qualitative Uncertainty in Protein Topology Prediction
    A Constraint Based Structure Description Language for Biosequences
    • 16
    • PDF


    Hybrid models of uncertainty in protein topology prediction
    • S. Parsons
    • Computer Science
    • Appl. Artif. Intell.
    • 1995
    • 4
    Probabilistic Prediction of Protein Secondary Structure Using Causal Networks (Extended Abstract)
    • 10
    • PDF
    Inductive Logic Programming Used to Discover Topological Constraints in Protein Structures
    • 6
    • PDF
    Heuristic refinement method for determination of solution structure of proteins from nuclear magnetic resonance data.
    • 34
    HMM with protein structure grammar
    • K. Asai, S. Hayamizu, K. Onizuka
    • Computer Science
    • [1993] Proceedings of the Twenty-sixth Hawaii International Conference on System Sciences
    • 1993
    • 37
    • PDF
    Prediction of the three‐dimensional structure of human growth hormone
    • 45