Gene Expression Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Gene Expression Analysis write by Nalini Raghavachari. This book was released on 2018-05-17. Gene Expression Analysis available in PDF, EPUB and Kindle. This volume provides experimental and bioinformatics approaches related to different aspects of gene expression analysis. Divided in three sections chapters detail wet-lab protocols, bioinformatics approaches, single-cell gene expression, highly multiplexed amplicon sequencing, multi-omics techniques, and targeted sequencing. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Gene Expression Analysis: Methods and Protocols aims provide useful information to researchers worldwide.
Gene Expression Data Analysis
Gene Expression Data Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Gene Expression Data Analysis write by Pankaj Barah. This book was released on 2021-11-08. Gene Expression Data Analysis available in PDF, EPUB and Kindle. Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systems A systematic overview of the methods for generating gene expression data Background knowledge on statistical modeling and machine learning techniques Detailed methodology of analyzing gene expression data with an example case study Clustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA data A large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patterns Suitable for multidisciplinary researchers and practitioners in computer science and the biological sciences
Molecular Pathology in Cancer Research
Molecular Pathology in Cancer Research - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Molecular Pathology in Cancer Research write by Sunil R. Lakhani. This book was released on 2017-01-20. Molecular Pathology in Cancer Research available in PDF, EPUB and Kindle. The aim of the book is to discuss the application of molecular pathology in cancer research, and its contribution in the classification of different tumors and identification of potential molecular targets, as well as how this knowledge may be translated into clinical practice, and the huge impact this field is likely to have in the next 5 to 10 years.
Statistical Analysis of Gene Expression Microarray Data
Statistical Analysis of Gene Expression Microarray Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Analysis of Gene Expression Microarray Data write by Terry Speed. This book was released on 2003-03-26. Statistical Analysis of Gene Expression Microarray Data available in PDF, EPUB and Kindle. Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists, geneticists, and computer scientists as well as statisticians all need an accessible, systematic treatment of the techniques used for analyzing the vast amounts of data generated by large-scale gene expression studies
Analyzing Microarray Gene Expression Data
Analyzing Microarray Gene Expression Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Analyzing Microarray Gene Expression Data write by Geoffrey J. McLachlan. This book was released on 2005-02-18. Analyzing Microarray Gene Expression Data available in PDF, EPUB and Kindle. A multi-discipline, hands-on guide to microarray analysis of biological processes Analyzing Microarray Gene Expression Data provides a comprehensive review of available methodologies for the analysis of data derived from the latest DNA microarray technologies. Designed for biostatisticians entering the field of microarray analysis as well as biologists seeking to more effectively analyze their own experimental data, the text features a unique interdisciplinary approach and a combined academic and practical perspective that offers readers the most complete and applied coverage of the subject matter to date. Following a basic overview of the biological and technical principles behind microarray experimentation, the text provides a look at some of the most effective tools and procedures for achieving optimum reliability and reproducibility of research results, including: An in-depth account of the detection of genes that are differentially expressed across a number of classes of tissues Extensive coverage of both cluster analysis and discriminant analysis of microarray data and the growing applications of both methodologies A model-based approach to cluster analysis, with emphasis on the use of the EMMIX-GENE procedure for the clustering of tissue samples The latest data cleaning and normalization procedures The uses of microarray expression data for providing important prognostic information on the outcome of disease
