1. Complex methods in clustering and classification
Techniques for the future
Worth “keep-trying”; But
No convincing evidence of dominant performance, globally or locally
Simplicity/complexity is crucial

2. Review Linkage : Eisen et al , Alon et al K-mean : Tavazoein et al
Self-organizing map : Tamayo et al
SVD : Holter et al; Alter, Brown, Botstein
Support vector machine (classification)

3. Finding Gene clusters K-mean versus self-organization map
how to fine-tune user-specified parameters-need some theoretical guidance
What is a cluster ? Criteria needed
normal mixture, (hidden) indicator
PLAID model ( Statistica Sinica 2002, Lazzeroni, Owen)
Gene shaving (Hastie, Tibshirani, et. al)
PCA plot, projection pursuit, grand tour
Y-guided clustering (SIR/PHD, under investigation)
MDS( bi-plot forcategorical responses, showing both cases (genes) and variables(different clustering methods), displaying results from many different clustering procedures)

4. Seriation and row-column sorting
Hierarchical clustering
Others
Generalized association plot (Chen 2001)
Sharp boundaries may be artifacts due to “clever” permutation