Percolation clustering: a novel approach to the clustering of gene expression patterns in Dictyostelium development.

@article{Ssik2001PercolationCA,
  title={Percolation clustering: a novel approach to the clustering of gene expression patterns in Dictyostelium development.},
  author={R. S{\'a}sik and Terence Hwa and N. Iranfar and W. F. Loomis},
  journal={Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing},
  year={2001},
  pages={335-47}
}
We present a novel approach to the clustering of gene expression patterns based on the mutual connectivity of the patterns. Unlike certain widely used methods (e.g., self-organizing maps and K-means) which essentially force gene expression data into a fixed number of predetermined clustering structures, our approach aims to reveal the natural tendency of the data to cluster, in analogy to the physical phenomenon of percolation. The approach is probabilistic in nature, and as such accommodates… CONTINUE READING