Microarray Gene Expression Data Analysis

This guide covers aspects of designing microarray experiments and analysing the data generated, including 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. Microarrays are an automated way of carrying out thousands of experiments at once, and allows scientists to obtain huge amounts of information very quickly Short, concise text on this difficult topic area Clear illustrations throughout Written by well-known teachers in the subject Provides insight into how to analyse the data produced from microarrays

Preface. Acknowledgements. 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. 10. Hybridisation. 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:. Index. Colour plates fall between pp. 84 and 85.