Microarray Gene Expression Data Analysis

Author: Helen Causton
Publisher: John Wiley & Sons
ISBN: 1444311565
Size: 43.23 MB
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This guide covers aspects of designing microarray experiments and analysing the data generated, including information on some of the tools that are available from non-commercial sources. Concepts and principles underpinning gene expression analysis are emphasised and wherever possible, the mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression. Microarrays are an automated way of carrying out thousands of experiments at once, and allows scientists to obtain huge amounts of information very quickly Short, concise text on this difficult topic area Clear illustrations throughout Written by well-known teachers in the subject Provides insight into how to analyse the data produced from microarrays

A Beginner S Guide To Microarrays

Author: Eric M. Blalock
Publisher: Springer Science & Business Media
ISBN: 1441987606
Size: 64.79 MB
Format: PDF
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A Beginner's Guide to Microarrays addresses two audiences - the core facility manager who produces, hybridizes, and scans arrays, and the basic research scientist who will be performing the analysis and interpreting the results. User friendly coverage and detailed protocols are provided for the technical steps and procedures involved in many facets of microarray technology, including: -Cleaning and coating glass slides, -Designing oligonucleotide probes, -Constructing arrays for the detection and quantification of different bacterial species, -Preparing spotting solutions, -Troubleshooting spotting problems, -Setting up and running a core facility, -Normalizing background signal and controlling for systematic variance, -Designing experiments for maximum effect, -Analyzing data with statistical procedures, -Clustering data with machine-learning protocols.

Analyzing Microarray Gene Expression Data

Author: Geoffrey McLachlan
Publisher: John Wiley & Sons
ISBN: 9780471726128
Size: 73.34 MB
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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

Statistical Analysis Of Gene Expression Microarray Data

Author: Terry Speed
Publisher: CRC Press
ISBN: 9780203011232
Size: 41.11 MB
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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. And there is arguably no group better qualified to do so than the authors of this book. Statistical Analysis of Gene Expression Microarray Data promises to become the definitive basic reference in the field. Under the editorship of Terry Speed, some of the world's most pre-eminent authorities have joined forces to present the tools, features, and problems associated with the analysis of genetic microarray data. These include:: Model-based analysis of oligonucleotide arrays, including expression index computation, outlier detection, and standard error applications Design and analysis of comparative experiments involving microarrays, with focus on \ two-color cDNA or long oligonucleotide arrays on glass slides Classification issues, including the statistical foundations of classification and an overview of different classifiers Clustering, partitioning, and hierarchical methods of analysis, including techniques related to principal components and singular value decomposition Although the technologies used in large-scale, high throughput assays will continue to evolve, statistical analysis will remain a cornerstone of their success and future development. Statistical Analysis of Gene Expression Microarray Data will help you meet the challenges of large, complex datasets and contribute to new methodological and computational advances.

Analysis Of Microarray Gene Expression Data

Author: Mei-Ling Ting Lee
Publisher: Springer Science & Business Media
ISBN: 1402077882
Size: 76.22 MB
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After genomic sequencing, microarray technology has emerged as a widely used platform for genomic studies in the life sciences. Microarray technology provides a systematic way to survey DNA and RNA variation. With the abundance of data produced from microarray studies, however, the ultimate impact of the studies on biology will depend heavily on data mining and statistical analysis. The contribution of this book is to provide readers with an integrated presentation of various topics on analyzing microarray data.

Microbial Functional Genomics

Author: Jizhong Zhou
Publisher: John Wiley & Sons
ISBN: 9780471071907
Size: 22.48 MB
Format: PDF, ePub, Mobi
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Genomics: toward a genome-level understanding of the structure, functions, and evolution of bioloical systems; Microbial diversity and genomics. Computational genome annotation. Microbial evolution from a genomics perspective. Computational methods for functional prediction of genes. DNA microarray technology. Microarray gene expression data analysis. Mutagenesis as a genomic tool for studying gene function. Mass spectrometry. Identification of protein-ligand interactions. The functional genomics of model organisms: addressing old questions from a new perspective. Functional genomic analysis of bacterial pathogens and environmentally significant microorganisms. The impact of genomics on antimicrobial drug discovery and toxicology. Application of microarray-based genomic technology to mutation analysis and microbial detection. Future perspectives: genomics beyond single cells.

Rna Methodologies

Author: Robert E. Farrell, Jr.
Publisher: Academic Press
ISBN: 0128046791
Size: 29.54 MB
Format: PDF, Kindle
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RNA Methodologies, Fifth Edition continues its tradition of excellence in providing the most up-to-date ribonucleic acid lab techniques for seasoned scientists and graduate students alike. This edition features new material on the exploding field of microRNA as well as the methods for the profiling of gene expression, both which have changed considerably in recent years. As a leader in the field, Dr. Farrell provides a wealth of knowledge on the topic of RNA while also giving readers helpful hints from his own personal experience in this subject area. Beginning with the most contemporary, RNA Methodologies, Fifth Edition, presents the essential techniques to use when working with RNA for the experienced practitioner while at the same time providing images and examples to aid the beginner in fully understanding this important branch of molecular biology. The next generation of scientists can look to this work as a guide for ensuring high productivity and highly representative data, as well as best practices in troubleshooting laboratory problems when they arise. Features new material in miRNA, MIQE guidelines, biomarkers, RNA sequencing, digital PCR and more Includes expanded coverage on quantitative PCR techniques, RNAi, bioinformatics, the role of locked nucleic acids, aptamer biology, PCR arrays, and other modern technologies Presents comprehensive, cutting-edge information covering all aspects of working with RNA Builds from basic information on RNA techniques to in-depth protocols to guidance on how to modify and adjust each step of a particular application Presents multiple avenues for addressing the same experimental goals

Bayesian Analysis Of Gene Expression Data

Author: Bani K. Mallick
Publisher: John Wiley & Sons
ISBN: 9780470742815
Size: 79.47 MB
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The field of high-throughput genetic experimentation is evolving rapidly, with the advent of new technologies and new venues for data mining. Bayesian methods play a role central to the future of data and knowledge integration in the field of Bioinformatics. This book is devoted exclusively to Bayesian methods of analysis for applications to high-throughput gene expression data, exploring the relevant methods that are changing Bioinformatics. Case studies, illustrating Bayesian analyses of public gene expression data, provide the backdrop for students to develop analytical skills, while the more experienced readers will find the review of advanced methods challenging and attainable. This book: Introduces the fundamentals in Bayesian methods of analysis for applications to high-throughput gene expression data. Provides an extensive review of Bayesian analysis and advanced topics for Bioinformatics, including examples that extensively detail the necessary applications. Accompanied by website featuring datasets, exercises and solutions. Bayesian Analysis of Gene Expression Data offers a unique introduction to both Bayesian analysis and gene expression, aimed at graduate students in Statistics, Biomedical Engineers, Computer Scientists, Biostatisticians, Statistical Geneticists, Computational Biologists, applied Mathematicians and Medical consultants working in genomics. Bioinformatics researchers from many fields will find much value in this book.

Gene Mapping Discovery And Expression

Author: Minou Bina
Publisher: Springer Science & Business Media
ISBN: 1597450979
Size: 36.46 MB
Format: PDF, Mobi
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A collection of cutting-edge computational tools and experimental techniques to study how genes are regulated, and to reconstruct the regulatory networks through which various cell-types are produced. On the computational side, web-based technologies to localize genes, to access and retrieve data from microarray databases, to conduct comparative genomics, and to discover the potential genomic DNA that may control the expression of protein-coding genes. Detailed experimental techniques described include methods for studying chromatin structure and allele-specific gene expression, methods for high-throughput analysis to characterize the transcription factor binding elements, and methods for isolating and identifying proteins that interact with DNA.

Bioinformatics For Beginners

Author: Supratim Choudhuri
Publisher: Elsevier
ISBN: 0124105106
Size: 69.83 MB
Format: PDF, Mobi
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Bioinformatics for Beginners: Genes, Genomes, Molecular Evolution, Databases and Analytical Tools provides a coherent and friendly treatment of bioinformatics for any student or scientist within biology who has not routinely performed bioinformatic analysis. The book discusses the relevant principles needed to understand the theoretical underpinnings of bioinformatic analysis and demonstrates, with examples, targeted analysis using freely available web-based software and publicly available databases. Eschewing non-essential information, the work focuses on principles and hands-on analysis, also pointing to further study options. Avoids non-essential coverage, yet fully describes the field for beginners Explains the molecular basis of evolution to place bioinformatic analysis in biological context Provides useful links to the vast resource of publicly available bioinformatic databases and analysis tools Contains over 100 figures that aid in concept discovery and illustration