Model-Based Clustering with gene Ranking using penalized Mixtures of heavy-tailed Distributions

@article{Cozzini2013ModelBasedCW,
  title={Model-Based Clustering with gene Ranking using penalized Mixtures of heavy-tailed Distributions},
  author={Alberto Cozzini and Ajay Jasra and Giovanni Montana},
  journal={Journal of bioinformatics and computational biology},
  year={2013},
  volume={11 3},
  pages={
          1341007
        }
}
Cluster analysis of biological samples using gene expression measurements is a common task which aids the discovery of heterogeneous biological sub-populations having distinct mRNA profiles. Several model-based clustering algorithms have been proposed in which the distribution of gene expression values within each sub-group is assumed to be Gaussian. In the presence of noise and extreme observations, a mixture of Gaussian densities may over-fit and overestimate the true number of clusters… CONTINUE READING
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