Proven Methods for Big Data Analysis As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering Methods for Big and High-Dimensional Data Using R shows how to apply biclustering methods to find local patterns in a big data matrix. The book presents an overview of data analysis using biclustering methods from a practical point of view. Real case studies in drug discovery, genetics, marketing research, biology, toxicity, and sports illustrate the use of several biclustering methods. References to technical details of the methods are provided for readers who wish to investigate the full theoretical background. All the methods are accompanied with R examples that show how to conduct the analyses. The examples, software, and other materials are available on a supplementary website.

Proven Methods for Big Data Analysis As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering Methods for Big and High-Dimensional Data Using R shows how to apply biclustering methods to find local patterns in a big data matrix. The book presents an overview of data analysis using biclustering methods from a practical point of view. Real case studies in drug discovery, genetics, marketing research, biology, toxicity, and sports illustrate the use of several biclustering methods. References to technical details of the methods are provided for readers who wish to investigate the full theoretical background. All the methods are accompanied with R examples that show how to conduct the analyses. The examples, software, and other materials are available on a supplementary website.

The Affymetrix GeneChip (R) system is one of the most widely adapted microarray platforms. However, due to the overwhelming amount of information available, many Affymetrix users tend to stick to the default analysis settings and may end up drawing sub-optimal conclusions. Written by a molecular biologist and a biostatistician with a combined decade of experience in practical expression profiling experiments and data analyses, Gene Expression Studies Using Affymetrix Microarrays tears down the omnipresent language barriers among molecular biology, bioinformatics, and biostatistics by explaining the entire process of a gene expression study from conception to conclusion. Truly Multidisciplinary: Merges Molecular Biology, Bioinformatics, and Biostatistics This authoritative resource covers important technical and statistical pitfalls and problems, helping not only to explain concepts outside the domain of researchers, but to provide additional guidance in their field of expertise. The book also describes technical and statistical methods conceptually with illustrative, full-color examples, enabling those inexperienced with gene expression studies to grasp the basic principles. Gene Expression Studies Using Affymetrix Microarrays provides novices with a detailed, yet focused introductory course and practical user guide. Specialized experts will also find it useful as a translation dictionary to understand other involved disciplines or to get a broader picture of microarray gene expression studies in general. Although focusing on Affymetrix gene expression, this globally relevant guide covers topics that are equally useful for other microarray platforms and other Affymetrix applications.

The Affymetrix GeneChip (R) system is one of the most widely adapted microarray platforms. However, due to the overwhelming amount of information available, many Affymetrix users tend to stick to the default analysis settings and may end up drawing sub-optimal conclusions. Written by a molecular biologist and a biostatistician with a combined decade of experience in practical expression profiling experiments and data analyses, Gene Expression Studies Using Affymetrix Microarrays tears down the omnipresent language barriers among molecular biology, bioinformatics, and biostatistics by explaining the entire process of a gene expression study from conception to conclusion. Truly Multidisciplinary: Merges Molecular Biology, Bioinformatics, and Biostatistics This authoritative resource covers important technical and statistical pitfalls and problems, helping not only to explain concepts outside the domain of researchers, but to provide additional guidance in their field of expertise. The book also describes technical and statistical methods conceptually with illustrative, full-color examples, enabling those inexperienced with gene expression studies to grasp the basic principles. Gene Expression Studies Using Affymetrix Microarrays provides novices with a detailed, yet focused introductory course and practical user guide. Specialized experts will also find it useful as a translation dictionary to understand other involved disciplines or to get a broader picture of microarray gene expression studies in general. Although focusing on Affymetrix gene expression, this globally relevant guide covers topics that are equally useful for other microarray platforms and other Affymetrix applications.