Unsupervised Learning from Complex Data: Functional Genomic Clustering Applications

Ju Han Kim, M.D., Ph.D.

Harvard Medical School

March 14, 2001 4:00 pm

Organizing observation into meaningful structure is a fundamental mode of learning. Both hierarchical and partitional functional clustering of large-scale gene expression data play a key role in the analysis of DNA microarray experiments. The speaker will introduce novel clustering algorithms that organize high-dimensional space into lower-dimensional subspaces based on a strateforward geometric space-partitioning principle. A unified view of clustering principle and data visualization will be presented.

This page is maintained by Je-Gun Joung (jgjoung@scai.snu.ac.kr).
Last update: March 13, 2001