Classification Analysis Of Dna Microarrays
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| Author | : Leif E. Peterson |
| Publisher | : John Wiley & Sons |
| Total Pages | : 752 |
| Release | : 2013-06-24 |
| Genre | : Computers |
| ISBN | : 0470170816 |
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 | : Richard M. Simon |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 205 |
| Release | : 2006-05-09 |
| Genre | : Medical |
| ISBN | : 0387218661 |
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.
| Author | : Terry Speed |
| Publisher | : CRC Press |
| Total Pages | : 237 |
| Release | : 2003-03-26 |
| Genre | : Mathematics |
| ISBN | : 0203011236 |
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 | : Daniel P. Berrar |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 382 |
| Release | : 2007-05-08 |
| Genre | : Science |
| ISBN | : 0306478153 |
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 | : Mei-Ling Ting Lee |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 378 |
| Release | : 2007-05-08 |
| Genre | : Science |
| ISBN | : 1402077882 |
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.
| Author | : Dov Stekel |
| Publisher | : Cambridge University Press |
| Total Pages | : 296 |
| Release | : 2003-09-08 |
| Genre | : Medical |
| ISBN | : 9780521525879 |
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 | : Uwe R. Müller |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 388 |
| Release | : 2006-03-30 |
| Genre | : Medical |
| ISBN | : 3540265783 |
Ithasbeenstatedthatourknowledgedoublesevery20years,butthatmaybe an understatement when considering the Life Sciences. A series of discoveries and inventions have propelled our knowledge from the recognition that DNA isthegeneticmaterialtoabasicmolecularunderstandingofourselvesandthe living world around us in less than 50 years. Crucial to this rapid progress was thediscoveryofthedouble-helicalstructureofDNA,whichlaidthefoundation forallhybridizationbasedtechnologies. Thediscoveriesofrestrictionenzymes, ligases, polymerases, combined with key innovations in DNA synthesis and sequencing ushered in the era of biotechnologyas a new science with profound sociological and economic implications that are likely to have a dominating in?uence on the development of our society during this century. Given the process by which science builds on prior knowledge, it is perhaps unfair to single out a few inventions and credit them with having contributed most to thisavalancheofknowledge. Yet,therearesurelysomethatwillberecognized as having had a more profound impact than others, not just in the furthering of our scienti?c knowledge, but by leveraging commercial applications that provide a tangible return to our society. The now famous Polymerase Chain Reaction, or PCR, is surely one of those, as it has uniquely catalyzed molecular biology during the past 20 years, and continues to have a signi?cant impact on all areas that involve nucleic acids, ranging from molecular pathology to forensics. Ten years ago micro- ray technology emerged as a new and powerful tool to study nucleic acid - quences in a highly multiplexed manner, and has since found equally exciting and useful applications in the study of proteins, metabolites, toxins, viruses, whole cells and even tissues.
| Author | : Geoffrey J. McLachlan |
| Publisher | : John Wiley & Sons |
| Total Pages | : 366 |
| Release | : 2005-02-18 |
| Genre | : Mathematics |
| ISBN | : 0471726125 |
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
| Author | : Pierre Baldi |
| Publisher | : |
| Total Pages | : 213 |
| Release | : 2002 |
| Genre | : DNA microarrays |
| ISBN | : 9780511071676 |
DNA microarrays are revolutionizing biology and medicine. They can provide a snapshot of the level of gene expression in a cell and are therefore a powerful tool with which to study biological phenomena at the molecular level. This inter-disciplinary introduction will be essential reading for researchers of all disciplines.
| Author | : Verónica Bolón-Canedo |
| Publisher | : Humana |
| Total Pages | : 299 |
| Release | : 2019-05-22 |
| Genre | : Science |
| ISBN | : 9781493994410 |
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.
