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Zusatztext Praise for the First EditionThe 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. 74I 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. ?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 Informationen zum Autor Sorin Dra ghici the Robert J. Sokol MD Endowed Chair in Systems Biology in the Department of Obstetrics and Gynecology, professor in the Department of Clinical and Translational Science and Department of Computer Science, and head of the Intelligent Systems and Bioinformatics Laboratory at Wayne State University. He is also the chief of the Bioinformatics and Data Analysis Section in the Perinatology Research Branch of the National Institute for Child Health and Development. A senior member of IEEE, Dr. Draghici is an editor of IEEE/ACM Transactions on Computational Biology and Bioinformatics, Journal of Biomedicine and Biotechnology, and International Journal of Functional Informatics and Personalized Medicine . He earned a Ph.D. in computer science from the University of St. Andrews. Klappentext Richly illustrated in color, this bestselling text provides a clear and rigorous description of powerful analysis techniques and algorithms for mining and interpreting biological information. Omitting tedious details, heavy formalisms, and cryptic notations, the text takes a hands-on, example-based approach that explains the basics of R and micr Zusammenfassung Richly illustrated in color, this bestselling text provides a clear and rigorous description of powerful analysis techniques and algorithms for mining and interpreting biological information. Omitting tedious details, heavy formalisms, and cryptic notations, the text takes a hands-on, example-based approach that explains the basics of R and micr Inhaltsverzeichnis Introduction. The Cell and Its Basic Mechanisms. Microarrays. Reliability and Reproducibility Issues in DNA Microarray Measurements. Image Processing. Introduction to R. Bioconductor: Principles and Illustrations. Elements of Statistics. Probability Distributions. Basic Statistics in R. Statistical Hypothesis Testing. Classical Approaches to Data Analysis. Analysis of Variance (ANOVA). Linear Models in R. Experiment Design. Multiple Comparisons. Analysis and Visualization Tools. Cluster Analysis. Quality Control. Data Pre-Processing and Normalization. Methods for Selecting Differentially Regulated Genes. The Gene Ontology (GO). Functional Analysis and Biological Interpretation of Microarray Data. Uses, Misuses, and Abuses in GO Profiling. A Comparison of Several Tools for Ontological Analysis. Focused Microarrays — Comparison and Selection. ID Mapping Issues. Pathway Analysis. Machine Learning Techniques. The Road Ahead. References. ...
