Isbn: 9783030733506 - statistical analysis of microbiome data (frontiers in probability and the statistical sciences) (2 Ergebnisse)

ISBN
Mit der Detailsuche verfeinern

Optimieren Sie Ihre Suche

  • Bücher (2)

  • Neu (2)

bis

Benutzerdefinierte Preisspanne (EUR)

bis

    • Sprache: Englisch

      Verlag: Springer, 2021

      3030733505 / 9783030733506

      • Hardcover

      Anbieter: Brook Bookstore, Milano, MI, ItalienBrook Bookstore

      Verkäufer/-in mit 5 Sternen
      Verkäufer/-in kontaktieren

      Zustand: Neu

      EUR 97,52

      EUR 27,99 Versand 
      Versand von Italien nach USA

      Anzahl: 5 verfügbar

      Zustand: new.

    • Sprache: Englisch

      Verlag: Springer International Publishing, 2021

      3030733505 / 9783030733506

      • Hardcover

      Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

      Verkäufer/-in mit 5 Sternen
      Verkäufer/-in kontaktieren

      Zustand: Neu

      EUR 140,65

      EUR 30,50 Versand 
      Versand von Deutschland nach USA

      Anzahl: 1 verfügbar

      Buch. Zustand: 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.