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