Trajectory Clustering: A Non-Parametric Method for Grouping Gene Expression Time Courses with Applications to Mammary Development

@article{Phang2003TrajectoryCA,
  title={Trajectory Clustering: A Non-Parametric Method for Grouping Gene Expression Time Courses with Applications to Mammary Development},
  author={Tzu L. Phang and Margaret C. Neville and Michael Rudolph and Lawrence Hunter},
  journal={Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing},
  year={2003},
  pages={351-62}
}
Trajectory clustering is a novel and statistically well-founded method for clustering time series data from gene expression arrays. Trajectory clustering uses non-parametric statistics and is hence not sensitive to the particular distributions underlying gene expression data. Each cluster is clearly defined in terms of direction of change of expression for successive time points (its 'trajectory'), and therefore has easily appreciated biological meaning. Applying the method to a dataset from… CONTINUE READING