Publicado por Cham, Springer International Publishing., 2021
ISBN 10: 3030733505 ISBN 13: 9783030733506
Idioma: Inglés
Librería: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Alemania
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EUR 20,00
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Añadir al carrito1st ed. 2021. XIV, 346 p. Hardcover. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Frontiers in Probability and the Statistical Sciences. Sprache: Englisch.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 102,25
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Librería: Best Price, Torrance, CA, Estados Unidos de America
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Publicado por Springer Nature Switzerland AG, Cham, 2021
ISBN 10: 3030733505 ISBN 13: 9783030733506
Idioma: Inglés
Librería: Grand Eagle Retail, Mason, OH, Estados Unidos de America
EUR 138,07
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Añadir al carritoHardcover. Condición: new. Hardcover. Microbiome research has focused on microorganisms that live within the human body and their effects on health. During the last few years, the quantification of microbiome composition in different environments has been facilitated by the advent of high throughput sequencing technologies. The statistical challenges include computational difficulties due to the high volume of data; normalization and quantification of metabolic abundances, relative taxa and bacterial genes; high-dimensionality; multivariate analysis; the inherently compositional nature of the data; and the proper utilization of complementary phylogenetic information. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data.This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. In addition to reviewing demonstrably successful cutting-edge methods, particular emphasis is placed on examples in R that rely on available statistical packages for microbiome data. With its wide-ranging approach, the book benefits not only trained statisticians in academia and industry involved in microbiome research, but also other scientists working in microbiomics and in related fields. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data.This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 145,99
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Publicado por Springer Nature Switzerland AG, Cham, 2022
ISBN 10: 303073353X ISBN 13: 9783030733537
Idioma: Inglés
Librería: Grand Eagle Retail, Mason, OH, Estados Unidos de America
EUR 147,30
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Añadir al carritoPaperback. Condición: new. Paperback. Microbiome research has focused on microorganisms that live within the human body and their effects on health. During the last few years, the quantification of microbiome composition in different environments has been facilitated by the advent of high throughput sequencing technologies. The statistical challenges include computational difficulties due to the high volume of data; normalization and quantification of metabolic abundances, relative taxa and bacterial genes; high-dimensionality; multivariate analysis; the inherently compositional nature of the data; and the proper utilization of complementary phylogenetic information. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data.This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. In addition to reviewing demonstrably successful cutting-edge methods, particular emphasis is placed on examples in R that rely on available statistical packages for microbiome data. With its wide-ranging approach, the book benefits not only trained statisticians in academia and industry involved in microbiome research, but also other scientists working in microbiomics and in related fields. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data.This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 155,25
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 162,76
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Librería: Best Price, Torrance, CA, Estados Unidos de America
EUR 157,19
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 152,17
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 165,60
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Añadir al carritoCondición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 167,56
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Publicado por Springer Verlag, Singapore, Singapore, 2018
ISBN 10: 9811315337 ISBN 13: 9789811315336
Idioma: Inglés
Librería: Grand Eagle Retail, Mason, OH, Estados Unidos de America
EUR 170,24
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Añadir al carritoHardcover. Condición: new. Hardcover. This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research. The book also discusses recent developments in statistical modelling and data analysis in microbiome research, as well as the latest advances in next-generation sequencing and big data in methodological development and applications. This timely book will greatly benefit all readers involved in microbiome, ecology and microarray data analyses, as well as other fields of research. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 166,75
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 152,16
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 167,88
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 166,57
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Librería: California Books, Miami, FL, Estados Unidos de America
EUR 187,33
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 172,80
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Añadir al carritoCondición: New. 2021. Hardcover. . . . . .
Publicado por Springer International Publishing, 2022
ISBN 10: 303073353X ISBN 13: 9783030733537
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 128,39
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Microbiome research has focused on microorganisms that live within the human body and their effects on health. During the last few years, the quantification of microbiome composition in different environments has been facilitated by the advent of high throughput sequencing technologies. The statistical challenges include computational difficulties due to the high volume of data; normalization and quantification of metabolic abundances, relative taxa and bacterial genes; high-dimensionality; multivariate analysis; the inherently compositional nature of the data; and the proper utilization of complementary phylogenetic information. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data.This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. In addition to reviewing demonstrably successful cutting-edge methods, particular emphasis is placed on examples in R that rely on available statistical packages for microbiome data. With its wide-ranging approach, the book benefits not only trained statisticians in academia and industry involved in microbiome research, but also other scientists working in microbiomics and in related fields.
Publicado por Springer International Publishing, 2021
ISBN 10: 3030733505 ISBN 13: 9783030733506
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 128,39
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Microbiome research has focused on microorganisms that live within the human body and their effects on health. During the last few years, the quantification of microbiome composition in different environments has been facilitated by the advent of high throughput sequencing technologies. The statistical challenges include computational difficulties due to the high volume of data; normalization and quantification of metabolic abundances, relative taxa and bacterial genes; high-dimensionality; multivariate analysis; the inherently compositional nature of the data; and the proper utilization of complementary phylogenetic information. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data.This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. In addition to reviewing demonstrably successful cutting-edge methods, particular emphasis is placed on examples in R that rely on available statistical packages for microbiome data. With its wide-ranging approach, the book benefits not only trained statisticians in academia and industry involved in microbiome research, but also other scientists working in microbiomics and in related fields.