Subspace Weighting Co-Clustering of Gene Expression Data.

@article{Chen2017SubspaceWC,
  title={Subspace Weighting Co-Clustering of Gene Expression Data.},
  author={Xiaojun Chen and Joshua Zhexue Huang and Qingyao Wu and Min Yang},
  journal={IEEE/ACM transactions on computational biology and bioinformatics},
  year={2017}
}
Microarray technology enables the collection of vast amounts of gene expression data from biological experiments. Clustering algorithms have been successfully applied to exploring the gene expression data. Since a set of genes may be possible correlated to a subset of samples, it is useful to use co-clustering to recover co-clusters in the gene expression data. In this paper, we propose a novel algorithm, called Subspace Weighting Co-Clustering (SWCC), for high dimensional gene expression data… CONTINUE READING