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Preface.<br /> <br /> Acknowledgments.<br /> <br /> 1. Introduction.<br /> <br /> 2. Overview of Data Analysis.<br /> <br /> 3. Basic Data Analysis.<br /> <br /> 4. Visualization by Reduction of Dimensionality.<br /> <br /> 5. Cluster Analysis.<br /> <br /> 6. Beyond Cluster Analysis.<br /> <br /> 7. Reverse Engineering of Regulatory Networks.<br /> <br /> 8. Molecular Classifiers.<br /> <br /> 9. Selection of Genes for Spotting on Arrays.<br /> <br /> 10. Limitations of Expression Analysis.<br /> <br /> 11. Genotyping Chips.<br /> <br /> 12. Software Issues and Data Formats.<br /> <br /> 13. Commercial Software Packages.<br /> <br /> 14. Bibliography.<br /> <br /> Index.

"...a fine introduction to DNA microarray analysis using good concrete examples, well reasoned descriptions…and much-needed examination of the tools, technologies, and research resources...after reading this book, anyone new to microarray data should understand what can…be measured..." (<i>Nature Genetics</i>, Vol. 33, March 2003) <p>"...I'd recommend anyone setting out to use this methodology to buy a copy for the lab." (British Society for Cell Biology Newsletter)</p> <p>"...This useful little book .... I'd recommend anyone setting out to use this methodology to buy a copy for the lab." (British Society for Developmental Biology Newsletter)</p>

<b>Steen Knudsen</b> is Associate Professor and Deputy Director of the Center for Biological Sequence Analysis at the Technical University of Denmark. He received his Ph.D. from the University of Copenhagen in 1990 and joined the pioneers of bioinformatics with a publication in <i>Nature</i> that same year. His postdoctoral training in bioinformatics at Harvard University concerned computational gene finding in the human genome, and his current research is in the area of bioinformatics and genomics. He has been working with methods for analysis of DNA microarray data since 1998.

<p>Microarrays are low-density arrays of DNA molecules that permit many hybridization experiments to be performed in parallel. A Biologist's Guide to Analysis of DNA Microarray Data is the first authoritative text to focus on analysis (as opposed to technology) in diverse biological and medical applications of microarrays.</p> <p>Written for biologists without special training in data analysis and statistics, the Guide takes over where the image analysis software that accompanies DNA array equipment typically leaves off-with a file of signal intensities and fold changes compared to a control. The broad spectrum of established analysis approaches is covered, including cluster analysis, function prediction, and principal component analysis. A thorough, critical review of software programs is presented, and criteria for selecting programs are discussed. Each chapter contains a Further Reading section categorized by topic as well as a summary, and highlights numerous real examples to illustrate the key concepts. Chapter topics include:</p> <ul> <li>Basic data analysis</li> <li>Visualization by reduction of dimensionality<</li> <li>Cluster analysis of expression data</li> <li>Molecular classifiers</li> <li>Genotyping chips</li> <li>Software issues and data formats</li> </ul> <p><i>A Biologist's Guide to Analysis of DNA Microarray Data</i> meets the needs of research professionals, students, and trainees alike for a compact yet thorough guide to analyzing microarray data.</p>

"...provides a great introduction and overview of the computational methods associated with the anaylsis of microarray and chip data." - Gary Hardiman, Ph.D., Division of Biology, University of California San Diego, La Jolla, California

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