Microarray Bioinformatics PDF Download
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Author: Dov Stekel
Publisher: Cambridge University Press
ISBN: 9780521525879
Category : Medical
Languages : en
Pages : 296
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Book Description
This book is a comprehensive guide to all of the mathematics, statistics and computing you will need to successfully operate DNA microarray experiments. It is written for researchers, clinicians, laboratory heads and managers, from both biology and bioinformatics backgrounds, who work with, or who intend to work with microarrays. The book covers all aspects of microarray bioinformatics, giving you the tools to design arrays and experiments, to analyze your data, and to share your results with your organisation or with the international community. There are chapters covering sequence databases, oligonucleotide design, experimental design, image processing, normalisation, identifying differentially expressed genes, clustering, classification and data standards. The book is based on the highly successful Microarray Bioinformatics course at Oxford University, and therefore is ideally suited for teaching the subject at postgraduate or professional level.
Author: Dov Stekel
Publisher: Cambridge University Press
ISBN: 9780521525879
Category : Medical
Languages : en
Pages : 296
Get Book Here
Book Description
This book is a comprehensive guide to all of the mathematics, statistics and computing you will need to successfully operate DNA microarray experiments. It is written for researchers, clinicians, laboratory heads and managers, from both biology and bioinformatics backgrounds, who work with, or who intend to work with microarrays. The book covers all aspects of microarray bioinformatics, giving you the tools to design arrays and experiments, to analyze your data, and to share your results with your organisation or with the international community. There are chapters covering sequence databases, oligonucleotide design, experimental design, image processing, normalisation, identifying differentially expressed genes, clustering, classification and data standards. The book is based on the highly successful Microarray Bioinformatics course at Oxford University, and therefore is ideally suited for teaching the subject at postgraduate or professional level.
Author: Verónica Bolón-Canedo
Publisher: Humana
ISBN: 9781493994410
Category : Science
Languages : en
Pages : 299
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Book Description
This book provides a comprehensive, interdisciplinary collection of the main, up-to-date methods, tools, and techniques for microarray data analysis, covering the necessary steps for the acquisition of the data, its preprocessing, and its posterior analysis. Featuring perspectives from biology, computer science, and statistics, the volume explores machine learning methods such as clustering, feature selection, classification, data normalization, and missing value imputation, as well as the statistical analysis of the data and the most popular computer tools to analyze microarray data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will aid researchers in getting successful results. Cutting-edge and authoritative, Microarray Bioinformatics serves as an ideal guide for researchers and graduate students in bioinformatics, with basic knowledge in biology and computer science, and with a view to work with microarray datasets.
Author: Junbai Wang
Publisher: Humana Press
ISBN: 9781617793998
Category : Science
Languages : en
Pages : 401
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Book Description
Recent improvements in the efficiency, quality, and cost of genome-wide sequencing have prompted biologists and biomedical researchers to move away from microarray-based technology to ultra high-throughput, massively parallel genomic sequencing (Next Generation Sequencing, NGS) technology. In Next Generation Microarray Bioinformatics: Methods and Protocols, expert researchers in the field provide techniques to bring together current computational and statistical methods to analyze and interpreting both microarray and NGS data. These methods and techniques include resources for microarray bioinformatics, microarray data analysis, microarray bioinformatics in systems biology, next generation sequencing data analysis, and emerging applications of microarray and next generation sequencing. Written in the highly successful Methods in Molecular BiologyTM series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Authoritative and practical, Next Generation Microarray Bioinformatics: Methods and Protocols seeks to aid scientists in the further study of this crucially important research into the human DNA.
Author: Robert Gentleman
Publisher: Springer Science & Business Media
ISBN: 0387293620
Category : Computers
Languages : en
Pages : 478
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Book Description
Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.
Author: Helen Causton
Publisher: John Wiley & Sons
ISBN: 1444311565
Category : Science
Languages : en
Pages : 176
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Book Description
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
Author: Simon M. Lin
Publisher: Springer Science & Business Media
ISBN: 9780792375647
Category : Mathematics
Languages : en
Pages : 212
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Book Description
Papers from CAMDA 2000, December 18-19, 2000, Duke University, Durham, NC, USA
Author: Terry Speed
Publisher: CRC Press
ISBN: 0203011236
Category : Mathematics
Languages : en
Pages : 237
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Book Description
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
Author: Leif E. Peterson
Publisher: John Wiley & Sons
ISBN: 0470170816
Category : Computers
Languages : en
Pages : 752
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Book Description
Wiley Series in Bioinformatics: Computational Techniques and Engineering Yi Pan and Albert Y. Zomaya, Series Editors Wide coverage of traditional unsupervised and supervised methods and newer contemporary approaches that help researchers handle the rapid growth of classification methods in DNA microarray studies Proliferating classification methods in DNA microarray studies have resulted in a body of information scattered throughout literature, conference proceedings, and elsewhere. This book unites many of these classification methods in a single volume. In addition to traditional statistical methods, it covers newer machine-learning approaches such as fuzzy methods, artificial neural networks, evolutionary-based genetic algorithms, support vector machines, swarm intelligence involving particle swarm optimization, and more. Classification Analysis of DNA Microarrays provides highly detailed pseudo-code and rich, graphical programming features, plus ready-to-run source code. Along with primary methods that include traditional and contemporary classification, it offers supplementary tools and data preparation routines for standardization and fuzzification; dimensional reduction via crisp and fuzzy c-means, PCA, and non-linear manifold learning; and computational linguistics via text analytics and n-gram analysis, recursive feature extraction during ANN, kernel-based methods, ensemble classifier fusion. This powerful new resource: Provides information on the use of classification analysis for DNA microarrays used for large-scale high-throughput transcriptional studies Serves as a historical repository of general use supervised classification methods as well as newer contemporary methods Brings the reader quickly up to speed on the various classification methods by implementing the programming pseudo-code and source code provided in the book Describes implementation methods that help shorten discovery times Classification Analysis of DNA Microarrays is useful for professionals and graduate students in computer science, bioinformatics, biostatistics, systems biology, and many related fields.
Author: Daniel P. Berrar
Publisher: Springer Science & Business Media
ISBN: 0306478153
Category : Science
Languages : en
Pages : 382
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Book Description
In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.
Author: Richard M. Simon
Publisher: Springer Science & Business Media
ISBN: 0387218661
Category : Medical
Languages : en
Pages : 205
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Book Description
The analysis of gene expression profile data from DNA micorarray studies are discussed in this book. It provides a review of available methods and presents it in a manner that is intelligible to biologists. It offers an understanding of the design and analysis of experiments utilizing microarrays to benefit scientists. It includes an Appendix tutorial on the use of BRB-ArrayTools and step by step analyses of several major datasets using this software which is available from the National Cancer Institute.
