Since the advent of cDNA microarrays, oligonucleotide array technology, and gene chip analysis, genomics has revolutionized the entire field of biomedical research. A byproduct of this revolution, toxicogenomics is a fast-rising star within toxicological analysis.
Gathering together leading authors and scientists at the forefront of the field, An Introduction to Toxicogenomics provides a comprehensive overview of this new discipline. With a focus on toxicology, it introduces the basic principles of microarray/oligonucleotide array-based genomic analysis and explains how it fits into the field of biomedical research. These discussions provide an overview to the actual mechanics of the analyses themselves and offer insights on handling and quality control. Then the book features an important section on the basics of data analysis and clustering methods such as genetic algorithms. Finally, it covers the application of expression profiling in the field of toxicology and addresses the two fundamental types of analysis in detail, with sections dedicated to both mechanistic and predictive studies.
Although toxicogenomics promises fast, efficient techniques and information-rich data, much of its potential remains untapped. An Introduction to Toxicogenomics consolidates the concepts underlying the field to provide a solid foundation from which to begin your research endeavors.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Michael E. Burczynski
Gathering together leading authors and scientists at the forefront of the field, An Introduction to Toxicogenomics provides a comprehensive overview of this emerging subdiscipline. The book introduces the overall concept underlying microarray/oligonucleotide array-based genomic analysis and how it fits into the field of biomedical research. These discussions provide an overview of the actual mechanics of the analyses themselves and offer insights on handling and quality control. An important feature is the book's focus on the basics of data analysis and clustering methods, such as genetic algorithms, used for analyzing large-scale datasets derived from gene chip expression data.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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