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CBS >> CBS Courses >> NORFA 2004 >> Course Programme

Course Programme

Monday, May 17th - Introduction
10.00-10.30:
Introduction
10.30-11.30:
Short presentation of each course participant and their projects (max. 2 minutes each)
11.30-12.30:
Overview of Microarray Data Analysis
Steen Knudsen Lecture slides #1 Lecture slides #2
12.30-13.30:
Lunch and check in
13.30-15.40:
Introduction and Overview of Feature Selection, Classification and Class discovery
Jane Fridlyand Lecture slides
15.40-16.30:
Afternoon break
16.30-17.30:
Continued: Introduction and Overview of Feature Selection, Classification and Class discovery
Jane Fridlyand
17.30-18.00:
Check student labtops
18.30-
Dinner

Tuesday, May 18th - Feature Selection and Dimension Reduction
8.30-9.15:
Feature selection
Jane Fridlyand Lecture slides
9.15-11.00:
R/Bioconductor exercise in feature selection
Jane Fridlyand Exercise
(Exercise without solutions Solutions)
11.10-12.00:
Dimension Reduction Techniques for Classification: PCA and PLS
Anne-Laure Boulesteix Lecture slides Article1 Article2 Article3
12.00-13.00:
Lunch
13.00-15.00:
R/Bioconductor exercise in Dimension Reduction Techniques for Classification: PCA and PLS
Anne-Laure Boulesteix Exercise
15.05-
Excursion to Kronborg followed by dinner in Elsinore

Wednesday, May 19th - Classification
9.00-9.45:
Classification algorithms
Jane Fridlyand Lecture slides
9.45-11.15:
R/Bioconductor exercise in classification
Jane Fridlyand Exercise
(Exercise without solutions Solutions)
11.30-12.15:
Artificial Neural Networks and Classification
Carsten Peterson Lecture slides Article1 Article2
12.15-13.15:
Lunch
13.15-14.15:
Classification by Support Vector Machines and nearest shrunken centroid classification
Florian Markowetz Lecture slides Article
14.15-16.45:
R/Bioconductor exercise in Classification by SVM and PAMR
Florian Markowetz
Exercise Dataset
17.00-18.00:
Classification Validation and Optimisation
Huiru Zheng based on lecture notes by Francisco Azuaje Lecture slides Article
18.30-
Dinner

Thursday, May 20th - Class Discovery
9.00-10.30:
Validation and Visualisation of Expression Clustering Results, Automated Cluster Labelling and Class
Discovery
Huiru Zheng based on lecture notes by Francisco Azuaje Lecture slides
10.30-12.00:
Exercise in Validation and Visualisation of Expression Clustering Results, Automated Cluster Labelling and
Class Discovery
Huiru Zheng based on Java tool by Francisco Azuaje Exercise
12.00-13.00:
Lunch
13.00-14.00:
Bi-clustering
Yves Moreau Lecture slides Article
14.15-15.15:
Class Discovery with ISIS: Identifying Splits with Clear Separation in Gene Expression Data
Florian Markowetz Lecture slides Article
16.30-18.00:
R/Bioconductor exercise in Clustering Algorithms: K-means, PAM, Agglomerative, Divisive and Silhouettes
Anne-Laure Boulesteix Exercise
18.30-
Dinner followed by social gathering in the bar area

Friday, May 21st - Other Advances Topics in Microarray Data Analysis
-9.00:
Check out
9.00-9.50:
Meta-analysis of Microarray Data
Yves Moreau Lecture slides Article #1 Article #2
10.00-11.30:
Exercise in Meta-analysis
Yves Moreau Exercise Data vignette qvalue manual
11.45-12.30:
Extracting Pathway Activity from Gene Expression Data
Jean-Philippe Vert Lecture slides Article #1 Article #2
12.30-13.30:
Lunch
13.30-14.15:
Identifying Distinct Classes of Bladder Carcinoma
Lars Dyrskjøt Andersen Lecture slides Article
14.30-15.00:
Next Generation Microarray Technology: Overview of Febit Geniom One
Henrik Bjørn Nielsen Lecture slides
15.00-15.45:
Future Perspectives of Microarrays + Discussion
Steen Knudsen Lecture slides
15.45-16.15:
Evaluation of Course

Program subject to change without prior notice

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This file was last modified Monday 28th of June 2004 08:21:39 GMT