Biclustering of Expression Data

@article{Cheng2000BiclusteringOE,
  title={Biclustering of Expression Data},
  author={Yizong Cheng and George M. Church},
  journal={Proceedings. International Conference on Intelligent Systems for Molecular Biology},
  year={2000},
  volume={8},
  pages={
          93-103
        }
}
An efficient node-deletion algorithm is introduced to find submatrices in expression data that have low mean squared residue scores and it is shown to perform well in finding co-regulation patterns in yeast and human. This introduces "biclustering", or simultaneous clustering of both genes and conditions, to knowledge discovery from expression data. This approach overcomes some problems associated with traditional clustering methods, by allowing automatic discovery of similarity based on a… CONTINUE READING

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