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Paperback. Condizione: Very Good. In stock ready to dispatch from the UK.

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paperback. Condizione: Very Good.

Hardback. Condizione: Good. The interdisciplinary nature of bioinformatics presents a research challenge in integrating concepts, methods, software and multiplatform data. Although there have been rapid developments in new technology and an inundation of statistical methods for addressing other types of high-throughput data, such as proteomic profiles that arise from mass spectrometry experiments. This book discusses the development and application of Bayesian methods in the analysis of high-throughput bioinformatics data that arise from medical, in particular, cancer research, as well as molecular and structural biology. The Bayesian approach has the advantage that evidence can be easily and flexibly incorporated into statistical methods. A basic overview of the biological and technical principles behind multi-platform high-throughput experimentation is followed by expert reviews of Bayesian methodology, tools and software for single group inference, group comparisons, classification and clustering, motif discovery and regulatory networks, and Bayesian networks and gene interactions.…

Paperback. Condizione: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

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Condizione: New. Expert overviews of Bayesian methodology, tools and software for multi-platform high-throughput experimentation. Editor(s): Do, Kim-Anh; Muller, Peter; Vannucci, Marina. Num Pages: 456 pages, 22 tables. BIC Classification: PBT; PSAK. Category: (P) Professional & Vocational. Dimension: 220 x 140 x 25. Weight in Grams: 572. . 2012. Paperback. . . . . …

Condizione: New.

Hardback. Condizione: Good. The interdisciplinary nature of bioinformatics presents a research challenge in integrating concepts, methods, software and multiplatform data. Although there have been rapid developments in new technology and an inundation of statistical methods for addressing other types of high-throughput data, such as proteomic profiles that arise from mass spectrometry experiments. This book discusses the development and application of Bayesian methods in the analysis of high-throughput bioinformatics data that arise from medical, in particular, cancer research, as well as molecular and structural biology. The Bayesian approach has the advantage that evidence can be easily and flexibly incorporated into statistical methods. A basic overview of the biological and technical principles behind multi-platform high-throughput experimentation is followed by expert reviews of Bayesian methodology, tools and software for single group inference, group comparisons, classification and clustering, motif discovery and regulatory networks, and Bayesian networks and gene interactions.…

Condizione: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Condizione: New. pages cm.

Condizione: New.

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Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.

Condizione: New.

Condizione: New. pages cm First edition Includes bibliographical references and index.

Condizione: New. Expert overviews of Bayesian methodology, tools and software for multi-platform high-throughput experimentation. Editor(s): Do, Kim-Anh; Muller, Peter; Vannucci, Marina. Num Pages: 456 pages, 22 tables. BIC Classification: PBT; PSAK. Category: (P) Professional & Vocational. Dimension: 220 x 140 x 25. Weight in Grams: 572. . 2012. Paperback. . . . . Books ship from the US and Ireland. …

Paperback. Condizione: Brand New. 1st edition. 456 pages. 8.58x5.51x1.02 inches. In Stock.

Condizione: New. In English.

Paperback. Condizione: New. Bayesian variable selection has experienced substantial developments over the past 30 years with the proliferation of large data sets. Identifying relevant variables to include in a model allows simpler interpretation, avoids overfitting and multicollinearity, and can provide insights into the mechanisms underlying an observed phenomenon. Variable selection is especially important when the number of potential predictors is substantially larger than the sample size and sparsity can reasonably be assumed.The Handbook of Bayesian Variable Selection provides a comprehensive review of theoretical, methodological and computational aspects of Bayesian methods for variable selection. The topics covered include spike-and-slab priors, continuous shrinkage priors, Bayes factors, Bayesian model averaging, partitioning methods, as well as variable selection in decision trees and edge selection in graphical models. The handbook targets graduate students and established researchers who seek to understand the latest developments in the field. It also provides a valuable reference for all interested in applying existing methods and/or pursuing methodological extensions.Features:Provides a comprehensive review of methods and applications of Bayesian variable selection.Divided into four parts: Spike-and-Slab Priors; Continuous Shrinkage Priors; Extensions to various Modeling; Other Approaches to Bayesian Variable Selection.Covers theoretical and methodological aspects, as well as worked out examples with R code provided in the online supplement. Includes contributions by experts in the field.Supported by a website with code, data, and other supplementary material.…

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The interdisciplinary nature of bioinformatics presents a research challenge in integrating concepts, methods, software and multiplatform data. Although there have been rapid developments in new technology and an inundation of statistical methods for addressing other types of high-throughput data, such as proteomic profiles that arise from mass spectrometry experiments. This book discusses the development and application of Bayesian methods in the analysis of high-throughput bioinformatics data that arise from medical, in particular, cancer research, as well as molecular and structural biology. The Bayesian approach has the advantage that evidence can be easily and flexibly incorporated into statistical methods. A basic overview of the biological and technical principles behind multi-platform high-throughput experimentation is followed by expert reviews of Bayesian methodology, tools and software for single group inference, group comparisons, classification and clustering, motif discovery and regulatory networks, and Bayesian networks and gene interactions.…

Condizione: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Paperback. Condizione: Brand New. 490 pages. 10.00x7.00x1.11 inches. In Stock.

Taschenbuch. Condizione: Neu. Handbook of Bayesian Variable Selection | Mahlet G. Tadesse (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | Chapman and Hall/CRC | EAN 9780367543785 | Verantwortliche Person für die EU: Taylor and Francis, Taylor & Francis Verlag Gmbh, Kaufingerstr 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu. …

Hardcover. Condizione: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condizione: New.

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Condizione: As New. Unread book in perfect condition.

Gebunden. Condizione: New.

Condizione: New.