Improving biomolecular pattern discovery and visualization with hybrid self-adaptive networks.

@article{Wang2002ImprovingBP,
  title={Improving biomolecular pattern discovery and visualization with hybrid self-adaptive networks.},
  author={Haiying Wang and Francisco Azuaje and Norman David Black},
  journal={IEEE transactions on nanobioscience},
  year={2002},
  volume={1 4},
  pages={
          146-66
        }
}
There is an increasing need to develop powerful techniques to improve biomedical pattern discovery and visualization. This paper presents an automated approach, based on hybrid self-adaptive neural networks, to pattern identification and visualization for biomolecular data. The methods are tested on two datasets: leukemia expression data and DNA splice-junction sequences. Several supervised and unsupervised models are implemented and compared. A comprehensive evaluation study of some of their… CONTINUE READING
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An integrative and interactive framework for improving biomedical pattern discovery and visualization

  • IEEE Transactions on Information Technology in Biomedicine
  • 2004
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  • 2010 Fifth International Conference on Information and Automation for Sustainability
  • 2010

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