Data Analysis Tools for DNA Microarrays
Will be published approx. on 4. June 2003
552 pages
E-Book
978-0-429-52415-8 (ISBN)
Description
Technology today allows the collection of biological information at an unprecedented level of detail and in increasingly vast quantities. To reap real knowledge from the mountains of data produced, however, requires interdisciplinary skills-a background not only in biology but also in computer science and the tools and techniques of data analysis.
Reviews / Votes
"The book by Draghici is an excellent choice to be used as a textbook for a graduate level bioinformatics course. This well-written book with two accompanying CD-ROMs will create much needed enthusiasm among statisticians."-Journal of Statistical Computation and Simulation, Vol. 74
"I really like Draghici's book. As the author explains in the Preface, the book is intended to serve both the statistician who knows very little about DNA microarrays and the biologist who has no expertise in data analysis. The author lays out a study plan for the statistician that excludes 5 of the 17 chapters (4-8). These chapters present the basics of statistical distributions, estimation, hypothesis testing, ANOVA, and experimental design. What that leaves for the statistician is the three-chapter primer on microarrays and image processing, plus all of the data analysis tools specific to the microarray situation.
"The softcover book is reasonably priced, and it includes two CDs with trial versions of several specialised software packages. Anyone who uses microarray data should certainly own a copy."
-Technometrics, Vol. 47, No. 1, February 2005
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
ISBN-13
978-0-429-52415-8 (9780429524158)
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Schweitzer Classification
Other editions
Additional editions
Sorin Draghici
Data Analysis Tools for DNA Microarrays
Book
06/2003
1st Edition
Chapman & Hall/CRC
€103.07
Article exhausted; check for reprint
Person
Content
Introduction. Microarrays. Image Processing. Elements of Statistics. Statistical Hypothesis Testing. Classical Approaches to Data Analysis. Analysis of Variance-ANOVA. Experiment Design. Multiple Comparisons. Analysis and Visualization Tools. Cluster Analysis. Data Pre-Processing and Normalization. Methods for Selecting Differentially Regulated Genes. Functional Analysis and Biological Interpretation of Microarray Data. Focused Microarrays--Comparison and Selection. Commercial Applications. The Road Ahead. References.
