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Microarray Data Analysis

Methods and Applications

  • Book
  • © 2016

Overview

Editors:
  1. Pietro Hiram Guzzi

    1. Department of Surgical and Medical Sciences, University “Magna Græcia” of Catanzaro, Catanzaro, Italy

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  • Includes cutting-edge methods and protocols
  • Provides step-by-step detail essential for reproducible results
  • Contains key notes and implementation advice from the experts

Part of the book series: Methods in Molecular Biology (MIMB, volume 1375)

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Table of contents (17 protocols)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Normalization of Affymetrix miRNA Microarrays for the Analysis of Cancer Samples

    • Di Wu, Michael P. Gantier
    Pages 1-10

  3. Methods and Techniques for miRNA Data Analysis

    • Francesca Cristiano, Pierangelo Veltri
    Pages 11-23

  4. Bioinformatics and Microarray Data Analysis on the Cloud

    • Barbara Calabrese, Mario Cannataro
    Pages 25-39

  5. Classification and Clustering on Microarray Data for Gene Functional Prediction Using R

    • Liliana López Kleine, Rosa Montaño, Francisco Torres-Avilés
    Pages 41-54

  6. Querying Co-regulated Genes on Diverse Gene Expression Datasets Via Biclustering

    • Mehmet Deveci, Onur Küçüktunç, Kemal Eren, Doruk Bozdağ, Kamer Kaya, Ümit V. Çatalyürek
    Pages 55-74

  7. MetaMirClust: Discovery and Exploration of Evolutionarily Conserved miRNA Clusters

    • Wen-Ching Chan, Wen-chang Lin
    Pages 75-89

  8. Analysis of Gene Expression Patterns Using Biclustering

    • Swarup Roy, Dhruba K. Bhattacharyya, Jugal K. Kalita
    Pages 91-103

  9. Using Semantic Similarities and csbl.go for Analyzing Microarray Data

    • Kristian Ovaska
    Pages 105-116

  10. Ontology-Based Analysis of Microarray Data

    • Agapito Giuseppe, Marianna Milano
    Pages 117-121

  11. Integrated Analysis of Transcriptomic and Proteomic Datasets Reveals Information on Protein Expressivity and Factors Affecting Translational Efficiency

    • Jiangxin Wang, Gang Wu, Lei Chen, Weiwen Zhang
    Pages 123-136

  12. Integrating Microarray Data and GRNs

    • L. Koumakis, G. Potamias, M. Tsiknakis, M. Zervakis, V. Moustakis
    Pages 137-153

  13. Biological Network Inference from Microarray Data, Current Solutions, and Assessments

    • Swarup Roy, Pietro Hiram Guzzi
    Pages 155-167

  14. A Protocol to Collect Specific Mouse Skeletal Muscles for Metabolomics Studies

    • Zhuohui Gan, Zhenxing Fu, Jennifer C. Stowe, Frank L. Powell, Andrew D. McCulloch
    Pages 169-179

  15. Functional Analysis of microRNA in Multiple Myeloma

    • Maria Teresa Di Martino, Nicola Amodio, Pierfrancesco Tassone, Pierosandro Tagliaferri
    Pages 181-194

  16. Microarray Analysis in Glioblastomas

    • Kaumudi M. Bhawe, Manish K. Aghi
    Pages 195-206

  17. Analysis of microRNA Microarrays in Cardiogenesis

    • Diego Franco, Fernando Bonet, Francisco Hernandez-Torres, Estefania Lozano-Velasco, Francisco J. Esteban, Amelia E. Aranega
    Pages 207-221

  18. Erratum to: Classification and Clustering on Microarray Data for Gene Functional Prediction Using R

    • Liliana López Kleine, Rosa Montaño, Francisco Torres-Avilés
    Pages 223-223

  19. Back Matter

    Pages 225-226
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Keywords

About this book

This volume covers a large area, from the description of methodologies for data analysis to the real application. Chapters focus on methodologies for preprocessing of microarray data, a survey of miRNA Data analysis, Cloud-based approaches, application of data mining techniques for data analysis, biclustering to query different datasets, web-based tool to analyze the evolution of miRNA clusters, application of biclustering to mine patterns of co-regulated genes ontologies, microarray and proteomic Data, Gene Regulatory Network Inference, Gene Regulatory Network methods, analysis of Mouse data for metabolomics studies, analysis of microRNA data in Multiple Myeloma, microarray data analysis in Gliobastomas, and microRNA data in Cardiogenesis.Written for the Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Authoritative and practical, Microarray Data Analysis: Methods and Applications, Second Edition aims to ensure successful results in the further study of this vital field.

Editors and Affiliations

  • Department of Surgical and Medical Sciences, University “Magna Græcia” of Catanzaro, Catanzaro, Italy

    Pietro Hiram Guzzi

Bibliographic Information

  • Book Title: Microarray Data Analysis

  • Book Subtitle: Methods and Applications

  • Editors: Pietro Hiram Guzzi

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-4939-3173-6

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: Springer Science+Business Media, LLC, part of Springer Nature 2016

  • Hardcover ISBN: 978-1-4939-3172-9Published: 23 February 2016

  • Softcover ISBN: 978-1-4939-7993-6Published: 13 March 2019

  • eBook ISBN: 978-1-4939-3173-6Published: 22 February 2016

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 2

  • Number of Pages: XI, 226

  • Number of Illustrations: 15 b/w illustrations, 5 illustrations in colour

  • Topics: Bioinformatics

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