CLIC is web server application for clustering large size of microarray dataset
with high accuracy and automatic determination of cluster number.


CLIC has following features
  • parallelized computation of sample-wise clustering

  • automatic determination of the number of clusters

  • intrinsic normalization of expression values among samples and clusters using the ordinal labeling of a cluster in a sample

  • evaluation of discovered clusters with cluster homogeneity.

  • identification and grouping of the common expression profile patterns of genes

  • visual inspection of discovered clusters and patterns using a heatmap

  • functional enrichment of each cluster and pattern.

  • Menu descriptions
  • Home: Index page of CLIC. It explains various features of CLIC.

  • Analysis: Analysis page of CLIC. It also provides example datasets and example outputs.

  • Tutorial: Explain analysis of CLIC step by step with graphical aid.

  • Help: Brief description of algorithms used in CLIC.

  • Contact: E-mail address.

    Citation: T. Yun et al., "CLIC: clustering analysis of large microarray datasets with individual dimension-based clustering", Nucl. Acids Res. (2010) 38 (suppl 2): W246-W253
  • Admin   Bioinformatics and Synthetic Biology Lab.    KAIST