Microarray Data Analysis

Giuseppe Agapito

ISBN 10: 1071618385 / ISBN 13: 9781071618387

Published by Springer US, Springer US, 2021

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This meticulous book explores the leading methodologies, techniques, and tools for microarray data analysis, given the difficulty of harnessing the enormous amount of data. The book includes examples and code in R, requiring only an introductory computer science understanding, and the structure and the presentation of the chapters make it suitable for use in bioinformatics courses. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of key detail and expert implementation advice that ensures successful results and reproducibility.Authoritative and practical, Microarray Data Analysis is an ideal guide for students or researchers who need to learn the main research topics and practitioners who continue to work with microarray datasets.

Seller Inventory # 9781071618387

Bibliographic Details

• Title: Microarray Data Analysis
• Publisher: Springer US, Springer US
• Publication Date: 2021
• Language: English
• ISBN 10: 1071618385
• ISBN 13: 9781071618387
• Binding: Buch
• Condition: Neu
• Dimensions: 260W x 183H x 24D millimeters 260 millimeters width by 183 millimeters height by 24 millimeters depth
• Weight: 823 grams

About this title

Synopsis

This meticulous book explores the leading methodologies, techniques, and tools for microarray data analysis, given the difficulty of harnessing the enormous amount of data. The book includes examples and code in R, requiring only an introductory computer science understanding, and the structure and the presentation of the chapters make it suitable for use in bioinformatics courses. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of key detail and expert implementation advice that ensures successful results and reproducibility. 

Authoritative and practical, Microarray Data Analysis is an ideal guide for students or researchers who need to learn the main research topics and practitioners who continue to work with microarray datasets.