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MicroRNA Detection and Target Identification

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Cover of 'MicroRNA Detection and Target Identification'

Table of Contents

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    Book Overview
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    Chapter 1 Improved Denaturation of Small RNA Duplexes and Its Application for Northern Blotting
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    Chapter 2 High-Throughput RT-qPCR for the Analysis of Circulating MicroRNAs
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    Chapter 3 Genome-Wide Comparison of Next-Generation Sequencing and qPCR Platforms for microRNA Profiling in Serum
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    Chapter 4 Small RNA Profiling by Next-Generation Sequencing Using High-Definition Adapters
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    Chapter 5 Surface Acoustic Wave Lysis and Ion-Exchange Membrane Quantification of Exosomal MicroRNA
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    Chapter 6 Droplet Microfluidic Device Fabrication and Use for Isothermal Amplification and Detection of MicroRNA
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    Chapter 7 Interrogation of Functional miRNA–Target Interactions by CRISPR/Cas9 Genome Engineering
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    Chapter 8 Cell-Free Urinary MicroRNAs Expression in Small-Scale Experiments
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    Chapter 9 Peptide-Based Isolation of Argonaute Protein Complexes Using Ago-APP
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    Chapter 10 Predicting Functional MicroRNA-mRNA Interactions
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    Chapter 11 Computational and Experimental Identification of Tissue-Specific MicroRNA Targets
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    Chapter 12 sRNAtoolboxVM: Small RNA Analysis in a Virtual Machine
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    Chapter 13 An Assessment of the Next Generation of Animal miRNA Target Prediction Algorithms
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    Chapter 14 The UEA Small RNA Workbench: A Suite of Computational Tools for Small RNA Analysis
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    Chapter 15 Prediction of miRNA–mRNA Interactions Using miRGate
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    Chapter 16 Detection of microRNAs Using Chip-Based QuantStudio 3D Digital PCR
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    Chapter 17 MiRNA Quantitation with Microelectrode Sensors Enabled by Enzymeless Electrochemical Signal Amplification
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    Chapter 18 A Robust Protocol to Quantify Circulating Cancer Biomarker MicroRNAs
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    Chapter 19 MicroRNAs, Regulatory Networks, and Comorbidities: Decoding Complex Systems
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    Chapter 20 Label-Free Direct Detection of MiRNAs with Poly-Silicon Nanowire Biosensors
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    Chapter 21 Erratum to: Cell-Free Urinary MicroRNAs Expression in Small-Scale Experiments
Attention for Chapter 10: Predicting Functional MicroRNA-mRNA Interactions
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Chapter title
Predicting Functional MicroRNA-mRNA Interactions
Chapter number 10
Book title
MicroRNA Detection and Target Identification
Published in
Methods in molecular biology, April 2017
DOI 10.1007/978-1-4939-6866-4_10
Pubmed ID
Book ISBNs
978-1-4939-6864-0, 978-1-4939-6866-4
Authors

Zixing Wang, Yin Liu

Editors

Tamas Dalmay

Abstract

MicroRNAs (miRNAs) are small RNA molecules that play key regulatory roles in general biological processes and disease pathogenesis. These small RNA molecules interact with their target mRNAs to induce mRNA degradation and/or inhibit the translation of mRNAs into proteins. Therefore, identifying miRNA targets is an essential step to fully understand the regulatory effects of miRNAs. Here, we describe a regularized regression approach that integrates the sequence information with the miRNA and mRNA expression profiles for detecting miRNA targets. This method takes into account the full spectrum of gene sequence features of miRNA targets, including the thermodynamic stability, the accessibility energy, and the context features of the target sites,. Given these sequence features for each putative miRNA-mRNA interaction and their expression values, this model is able to quantify the down-regulation effect of each miRNA on its targets while simultaneously estimating the contribution of each sequence feature for predicting functional miRNA-mRNA interactions.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 40%
Professor 3 30%
Student > Master 1 10%
Unknown 2 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 40%
Environmental Science 1 10%
Agricultural and Biological Sciences 1 10%
Chemistry 1 10%
Unknown 3 30%