A short course on Computational and Statistical Aspects of Microarray Analysis
Kitasato University
July 14-25, 2003
Lecturer:
Robert Gentleman
Schedule of Topics
Monday, July 14 | Tuesday, July 15 | Wednesday, July 16 | Thursday, July 17 | Friday, July 18 | |
Lecture | Introduction to Genome Biology | R/S Programming Techniques | DNA Microarray Data, Oligonucleotide Arrays | Introduction to Bioconductor | Experimental Design and Experimental Design Paper |
Labs | Lecture Con't | Lab1, Lab2a | Lab2b | Lab3b | Estrogen |
Monday, July 21 | Tuesday, July 22 | Wednesday, July 23 | Thursday, July 24 | Friday, July 25 | |
Lecture | Holiday, No Lecture | Microarray Experiments and Distances and Expression Measures | Some Things Every Biologist Should Know About Machine Learning | Classification in Microarray Experiments | Clustering in Microarray Experiments |
Labs | Holiday | Lab4 | Lab5 | Lab6, Lab7 | Lab8 |
Lab materials
Lab1 | Bioconductor Basics | |||
Lab2a | Bioinformatics (anotation package) | |||
Lab2b | An Introduction to Some Graphics in Bioconductor | |||
Lab3a | Introduction to Bioconductor's marray Packages | |||
Lab3b | Introduction to the affy package | |||
Lab4 | Differential Gene Expression | |||
Lab5 | Cluster Analysis Using R and Bioconductor | |||
Lab6 | Classification Using R and Bioconductor | |||
Lab7 | Analyzing Microarray Data: From Images to List of Candidate Genes | |||
Lab8 | Application of Machine Learning to Microarray Data, SVM and friends |