Image from Google Jackets

Systems Biology in Animal Production and Health, Vol. 2 / edited by Haja N Kadarmideen

Contributor(s): SpringerLink (Online service) | Kadarmideen, Haja N., editor literario
Material type: materialTypeLabelE-bookPublisher: Cham : Springer International Publishing, 2016Description: 1 recurso en línea (XIII, 154 páginas) : 32 ilustraciones, 26 ilustraciones en color.ISBN: 9783319433325.Subject: Ciencias de la vida | BioinformáticaDDC classification: 591.35 Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Depicting gene co-expression networks underlying eQTLs -- Applications of systems biology to improve Pig health -- Computational methods for quality check, preprocessing and normalization of RNA-seq data for systems biology analysis -- Systems Biology Application in Feed Efficiency in Beef Cattle -- Nutritional systems biology to elucidate adaptations in lactation physiology of dairy cows -- Systems Biology and stem cell pluripotency; Revisiting the discovery of induced pluripotent stem cell
Abstract: This two-volume work provides an overview on various state of the art experimental and statistical methods, modeling approaches and software tools that are available to generate, integrate and analyze multi-omics datasets in order to detect biomarkers, genetic markers and potential causal genes for improved animal production and health. The book will contain online resources where additional data and programs can be accessed. Some chapters also come with computer programming codes and example datasets to provide readers hands-on (computer) exercises. This second volume deals with integrated modeling and analyses of multi-omics datasets from theoretical and computational approaches and presents their applications in animal production and health as well as veterinary medicine to improve diagnosis, prevention and treatment of animal diseases. This book is suitable for both students and teachers in animal sciences and veterinary medicine as well as to researchers in this discipline.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias de la Salud QH324.2 .S978 2016 EB (Browse shelf(Opens below)) .i11597926 Acceso electrónico eBOOK .i11597926
Total holds: 0

Depicting gene co-expression networks underlying eQTLs -- Applications of systems biology to improve Pig health -- Computational methods for quality check, preprocessing and normalization of RNA-seq data for systems biology analysis -- Systems Biology Application in Feed Efficiency in Beef Cattle -- Nutritional systems biology to elucidate adaptations in lactation physiology of dairy cows -- Systems Biology and stem cell pluripotency; Revisiting the discovery of induced pluripotent stem cell

This two-volume work provides an overview on various state of the art experimental and statistical methods, modeling approaches and software tools that are available to generate, integrate and analyze multi-omics datasets in order to detect biomarkers, genetic markers and potential causal genes for improved animal production and health. The book will contain online resources where additional data and programs can be accessed. Some chapters also come with computer programming codes and example datasets to provide readers hands-on (computer) exercises. This second volume deals with integrated modeling and analyses of multi-omics datasets from theoretical and computational approaches and presents their applications in animal production and health as well as veterinary medicine to improve diagnosis, prevention and treatment of animal diseases. This book is suitable for both students and teachers in animal sciences and veterinary medicine as well as to researchers in this discipline.

There are no comments on this title.

to post a comment.
Share