Session 1

1    14.10    Mats Rudemo
Spots shape modelling and saturated pixels in microarrays.

2    14.40    Chris Glasbey
Image analysis, normalisation and gene interaction modelling.

3    15.10    Phil Brain
A non-parametric variance-stabilising transformation for analysing micro-array data.        

Session 2

4    16.00    Ernst Wit
High dimensional analyses of gene expression data.

5    16.30    Dave Stephens    
Clustering of Anopheles gene expression profiles.

6    17.00    Chris Holmes
Detecting gene-gene interactions in microarray data using probabilistic rule sets


Session 3

7    09.00    Rafael Irizarry
Sequence Based Background Model for Affymetrix Arrays.

8    09.30    Wei Pan
On the use of permutation in detecting differential gene expression.

9    10.00    Anne-Mette Hein
Bayesian Hierarchical models for analysing Affymetrix gene expression arrays using probe level data.

10   10.20    Oliver Hartmann
Quality control for Affymetrix GeneChips: What MM’s are good for.

Session 4

11    11.10    Michael Newton
Differential expression analysis using hierarchical mixture models.

12    11.40    Alex Lewin
Bayesian hierarchical modelling of differential gene expression.

13    12.00    Annibale Biggeri
A Hierarchical Bayesian model to study temperature-dependent variation of sequence-specific hybridization to cDNA Microarray.

14    12.20    Renée Menezes
Hierarchical modelling to handle heteroscedasticity in microarray data.

Session 5

15    14.00    Geoff McLachlan
Classification of tissue samples on the basis of microarray gene-expression data.

16    14.30     Peter Green and Graeme Ambler
Bayesian Two-way clustering for gene expression data.

17    15.00    Bani Mallick
Bayesian classification of tumors using gene expression data.
18    15.20    Jelle Goeman    
Prediction with high-dimensional data using a model-based approach to dimension reduction.

Session 6

19    16.10    Mike West
Statistical trees and networks in clinical expression studies.
20    16.40    Giovanni Parmigiani
Cross-study validation and combined analysis of Molecular Classification data.

21    17.10    Phil Brown
Assessing differential gene expression using two-component microarray mixture models.

22    17.30    Colin Campbell
On the sample complexity of microarray data.


Session 7

23    09.00    Philippe Broët
Investigating genomic alterations from comparative genomic hybridization chip experiment using prior biological knowledge.    

24    09.30    Rolf Sundberg
Statistical methodology in case control 5’-nuclease assays for identification of differentially expressed genes.

25    09.50    Hans Van Houwelingen
Latent class analysis for Genomic Micro-arrays.

Session 8

26    10.40    Richard Simon
Design issues for studies using DNA Microarrays.

27    11.10    David Hoyle
Phylogenetic reconstruction from microarray data.
28    11.40    Terry Speed
To pool or not to pool: an experience with GeneChips.

Session 9

29    16.45    Marcel Dettling
Supervised clustering of genes

30    17.05    Ramon Diaz-Uriarte
A method for finding molecular signatures from gene expression data.

31    17.25    Yvonne Pittelkow    
Visualization methods for exploring microarray data.        


Byung Soo Kim
Detecting differentially expressed genes for the colorectal cancer: Combining paired data set with two independent data sets.