Microarray Gene Expression Data Analysis: A Beginner's Guide

ISBN-13: 9781405106825 / Angielski / Miękka / 2003 / 184 str.

Helen C. Causton; Alvis Brazma; John Quackenbush

Opis

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

Recenzje

"Quite a few recently published books discuss analysis of microarray gene expression data for beginners. Microarray Gene Expression Data Analysis ... is arguably the best of its kind in this regard." Terry Speed, The Walter & Eliza Hall Institute of Medical Research, Nature Cell Biology, December 2003 <!––end––>

"Overall this is an excellent book, it is well referenced and, to my mind, covers the vast majority of issues an experimenter needs to consider when venturing into the world of microarray data analysis. The book fills a clear gap in the field, providing a rigorous overview of the often confusing .... data analysis issues that most books on microarrays avoid or treat in a cursory way. I would say it is essential reading for any laboratory or researcher active in this rapidly evolving field and is recommended for the mathematician or statisitican who is interested in the field or who has been persuaded by their biologist colleague to help them with their analysis." Steven Russell, University of Cambridge, Genetical Research, February 2003

"Anyone wishing to gain a basic understanding of microarray gene expression studies will come away enriched ... A good and accessible entry point for any biologist who is interested in getting an overview about how to perform microarray gene expression studies." D.C.Jamison, George Mason University, Heredity, June 2004

Spis treści

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.

O autorze

Helen Causton is an experimental biologist who carried out some of the early studies on genome–wide transcriptional regulation in yeast using microarrays. She is Head of the Clinical Sciences Microarray Centre at Imperial College, University of London.

John Quackenbush is a principal investigator at The Institute for Genomic Research (TIGR). His research interests include development of software for microarray data analysis, gene indices and comparative genomics.

Alvis Brazma is a computer scientist who has been involved in microarray data analysis since 1998. He heads microarray informatics at the European Bioinformatics Institute and is in charge of establishing a public repository for microarray data.

Blurb

Microarray technology is arguably the most important recent breakthrough in molecular biology. It enables researchers to obtain snapshots of gene expression for all the genes in a genome in a single experiment. Microarray experiments generate massive amounts of data that can be analysed to extract new knowledge about the underlying biological processes.

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.