Clustering-based approaches to SAGE data mining

@article{Wang2008ClusteringbasedAT,
  title={Clustering-based approaches to SAGE data mining},
  author={Haiying Wang and Huiru Zheng and Francisco Azuaje},
  journal={BioData Mining},
  year={2008},
  volume={1},
  pages={5 - 5}
}
Serial analysis of gene expression (SAGE) is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical applications, such as the prediction of new gene functions and the identification of biomarkers in human cancer research. Clustering techniques have become fundamental approaches in these applications. This paper reviews relevant clustering techniques specifically designed for this type of data. It places an emphasis on… CONTINUE READING

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