ABSTRACT
The massive explosion of highly parallel sequence data has spurred the development of numerous computational methods for its analysis. These evolving next generation technologies enable the comprehensive analysis of larger transcriptomic data to be more robust, inexpensive, and widespread. Advancement in transcriptome analysis is becoming highly relevant in various biological studies, in particular the health care sector. The current chapter presents an overview of the methods currently available for transcriptome analysis, which includes microarrays and Ref-seq. The chapter also discusses various explorative and hypothesis driven applications of transcriptome data covering various diseases, molecular pathways, and clinical pharmacological investigations.
