A Comparison of Categorisation Algorithms for Predicting the Cellular Localisation Sites of Proteins

@inproceedings{Cairns2001ACO,
  title={A Comparison of Categorisation Algorithms for Predicting the Cellular Localisation Sites of Proteins},
  author={Paul A. Cairns and Christian R. Huyck and Ian M. Mitchell and Wendy Xihyu Wu},
  booktitle={DEXA Workshop},
  year={2001}
}
A previous attempt to categorize yeast proteins based on certain attributes yielded only a 55% success rate of correct categorisation using a new type of decision procedure [5]. This paper considers using existing soft computing approaches to improve the categorisation. More specifically, learning algorithms based on neural networks, growing cell systems, a rule development algorithm and genetic algorithms are applied to the yeast data. All of the results are at least as good as the original… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 10 references

Discovering Documents Associations Through Growing Cell Structures

  • W. X. Wu
  • International Conference on Artificial…
  • 2000
1 Excerpt

Discovering Relevant Knowledge for Clustering Through Incremental Growing Cell Structures

  • W. X. Wu, W. Dubitzky
  • Proc. of 2nd Int. Conf. on Data Fusion, 1999…
  • 1999
1 Excerpt

Neural Networks: A Comprehensive Foundation, 2nd edn

  • S. Haykin
  • 1999
1 Excerpt

Self-organising maps, 2nd edn, Springer-Verlag, Berlin

  • T. Kohonen
  • 1997
1 Excerpt

An Introduction to Genetic Algorithms

  • M. Mitchell
  • 1996
1 Excerpt

Fritake : ” Growing Cell Structures - A Self - Organising Network for Unsupervised and Supervised Learning ”

  • M. Kamber
  • Neural Networks

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