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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.
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.
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