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Microarray Data Analysis

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Cover of 'Microarray Data Analysis'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 236 Bioinformatics and Microarray Data Analysis on the Cloud.
  3. Altmetric Badge
    Chapter 237 MetaMirClust: Discovery and Exploration of Evolutionarily Conserved miRNA Clusters.
  4. Altmetric Badge
    Chapter 238 Methods and Techniques for miRNA Data Analysis.
  5. Altmetric Badge
    Chapter 239 Normalization of Affymetrix miRNA Microarrays for the Analysis of Cancer Samples.
  6. Altmetric Badge
    Chapter 240 Classification and Clustering on Microarray Data for Gene Functional Prediction Using R
  7. Altmetric Badge
    Chapter 241 Using Semantic Similarities and csbl.go for Analyzing Microarray Data
  8. Altmetric Badge
    Chapter 242 Integrated Analysis of Transcriptomic and Proteomic Datasets Reveals Information on Protein Expressivity and Factors Affecting Translational Efficiency
  9. Altmetric Badge
    Chapter 245 Microarray Analysis in Glioblastomas
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    Chapter 246 Querying Co-regulated Genes on Diverse Gene Expression Datasets Via Biclustering
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    Chapter 247 Analysis of microRNA Microarrays in Cardiogenesis.
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    Chapter 248 A Protocol to Collect Specific Mouse Skeletal Muscles for Metabolomics Studies
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    Chapter 249 Ontology-Based Analysis of Microarray Data
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    Chapter 250 Functional Analysis of microRNA in Multiple Myeloma.
  15. Altmetric Badge
    Chapter 252 Integrating Microarray Data and GRNs.
  16. Altmetric Badge
    Chapter 256 Erratum to: Classification and Clustering on Microarray Data for Gene Functional Prediction Using R
  17. Altmetric Badge
    Chapter 280 Analysis of Gene Expression Patterns Using Biclustering
  18. Altmetric Badge
    Chapter 284 Biological Network Inference from Microarray Data, Current Solutions, and Assessments.
Attention for Chapter 250: Functional Analysis of microRNA in Multiple Myeloma.
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Chapter title
Functional Analysis of microRNA in Multiple Myeloma.
Chapter number 250
Book title
Microarray Data Analysis
Published in
Methods in molecular biology, May 2015
DOI 10.1007/7651_2015_250
Pubmed ID
Book ISBNs
978-1-4939-3172-9, 978-1-4939-3173-6
Authors

Di Martino, Maria Teresa, Amodio, Nicola, Tassone, Pierfrancesco, Tagliaferri, Pierosandro, Maria Teresa Di Martino, Nicola Amodio, Pierfrancesco Tassone, Pierosandro Tagliaferri, Martino, Maria Teresa Di

Abstract

MicroRNAs (miRNAs) are short non coding RNAs that regulate the gene expression and play a relevant role in physiopathological mechanisms such as development, proliferation, death, and differentiation of normal and cancer cells. Recently, abnormal expression of miRNAs has been reported in most of solid or hematopoietic malignancies, including multiple myeloma (MM), where miRNAs have been found deeply dysregulated and act as oncogenes or tumor suppressors. Presently, the most recognized approach for definition of miRNA portraits is based on microarray profiling analysis. We here describe a workflow based on the identification of dysregulated miRNAs in plasma cells from MM patients based on Affymetrix technology. We describe how it is possible to search miRNA putative targets performing whole gene expression profile on MM cell lines transfected with miRNA mimics or inhibitors followed by luciferase reporter assay to analyze the specific targeting of the 3'untranslated region (UTR) sequence of a mRNA by selected miRNAs. These technological approaches are suitable strategies for the identification of relevant druggable targets in MM.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 25%
Researcher 2 13%
Student > Ph. D. Student 2 13%
Student > Bachelor 1 6%
Professor 1 6%
Other 5 31%
Unknown 1 6%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 38%
Agricultural and Biological Sciences 4 25%
Medicine and Dentistry 3 19%
Computer Science 1 6%
Unknown 2 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 May 2015.
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#20,271,607
of 22,803,211 outputs
Outputs from Methods in molecular biology
#9,905
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Outputs of similar age
#222,088
of 264,461 outputs
Outputs of similar age from Methods in molecular biology
#15
of 21 outputs
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