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Microarray Data Analysis de Giuseppe Agapito

Microarray Data Analysis: Methods in Molecular Biology, cartea 2401

Editat de Giuseppe Agapito
en Limba Engleză Paperback – 15 dec 2022
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.
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Specificații

ISBN-13: 9781071618417
ISBN-10: 1071618415
Pagini: 317
Ilustrații: XI, 317 p. 71 illus., 54 illus. in color.
Dimensiuni: 178 x 254 mm
Greutate: 0.58 kg
Ediția:1st ed. 2022
Editura: Springer Us
Colecția Humana
Seria Methods in Molecular Biology

Locul publicării:New York, NY, United States

Cuprins

Tools in Pharmacogenomics Biomarker Identification for Cancer Patients.- High Performance Framework to Analyze Microarray Data.- Web and Cloud Computing to Analyze Microarray Data.- A Microarray Analysis Technique Using a Self-Organizing Multi-Agent Approach.- Improving Analysis and Annotation of Microarray Data with Protein Interactions.- Algorithms to Preprocess Microarray Image Data.- Microarray Data Preprocessing: From Experimental Design to Differential Analysis.- Supervised Methods for Biomarker Detection from Microarray Experiments.- Unsupervised Algorithms for Microarray Sample Stratification.- Pathway Enrichment Analysis of Microarray Data.- Network Analysis of Microarray Data.- geneExpressionFromGEO: An R Package to Facilitate Data Reading from Gene Expression Omnibus (GEO).- Scenarios for the Integration of Microarray Gene Expression Profiles in COVID-19-Related Studies.- Alignment of Microarray Data.- Integration of DNA Microarray with Clinical and Genomic Data.- ClusteringMethods for Microarray Data Sets.- Microarray Data Analysis Protocol.- Using Gene Ontology to Annotate and Prioritize Microarray Data.- Using MMRFBiolinks R-Package for Discovering Prognostic Markers in Multiple Myeloma.

Textul de pe ultima copertă

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.

Caracteristici

Includes cutting-edge techniques Provides step-by-step detail essential for reproducible results Contain key implementation advice from the experts