This guide covers aspects of designing microarray experiments and analysing the data generated, and includes information on some of the tools that are available from non–commercial sources. Concepts and principles underpinning gene expression analysis are emphasised, and wherever possible the mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression.
Part I: Introduction:.
1. What Are Microarrays?.
2. Use Of Icroarrays To Monitor Gene Expression.
3. Other Uses For Microarrays.
4. Challenges Associated With The Generation Of Large Amounts Of Complex Data.
5. Future Directions.
Part II: Aspects Of Experimental Design:.
6. Features Of Microarray Data.
7. Designing The Best Experiment.
8. Preparation of Target.
9. Design of Spotted Arrays.
11. Long Term Considerations.
12. Verification of Results.
Part III: Data Analysis:.
13. Preliminary Processing of Data.
14. Methods for Data Analysis.
15. Graph Models.
16. Software In The Public Domain.
17. Visualisation of Data.
Part IV: Glossary:.
Colour plates fall between pp
84 and 85.