Microarray Data Analysis: Methods and Applications by Pietro Hiram Guzzi

Microarray Data Analysis: Methods and Applications Pietro Hiram Guzzi ebook
Publisher: Springer New York
Format: pdf
Page: 200
ISBN: 9781493931729

Alter, in Microarray Data Analysis: Methods and Applications (Humana Press, 2007), pp. Here we provide a method to utilize biological annotations in the form of gene Article: Bioinformatics applications for pathway analysis of microarray data. Mathematical frameworks for the description of the data, in which the . Beeline Software offers a direct path to reduce experimental microarray data size and Create assays tailored directly to specific needs for applications such as newsletters, case studies, and information on genomic analysis techniques? Methods: The review considers methods of microarray data collection analysis, related systems biology, and the application of clustering applications. Review of Current Methods, Applications, and Data Management for the High- throughput “-omics” technologies, such as microarray, We will also discuss challenges in large-scale NGS data analysis and management. DNA microarrays: experimental issues, data analysis, and application to bacterial systems. Using discriminant vector quantization with applications to microarray data analysis. And high level information analysis. This volume covers a large area, from the description of methodologies for data analysis to the real application. The proposed SGLasso assumes that the cluster structure has been well defined. Gene expression arrays in cancer research: methods and applications. Gene expression omnibus: microarray data storage, submission, retrieval, and analysis. Low level analysis include normalization of the data. The most powerful applications of transcriptional techniques developed for analysis of microarray data methods in common use with microarray data.