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Bioinformatics in MicroRNA Research

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Cover of 'Bioinformatics in MicroRNA Research'

Table of Contents

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    Book Overview
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    Chapter 1 MicroRNAs, Long Noncoding RNAs, and Their Functions in Human Disease
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    Chapter 2 MicroRNA Expression: Protein Participants in MicroRNA Regulation
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    Chapter 3 Viral MicroRNAs, Host MicroRNAs Regulating Viruses, and Bacterial MicroRNA-Like RNAs
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    Chapter 4 MicroRNAs: Biomarkers, Diagnostics, and Therapeutics
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    Chapter 5 Relational Databases and Biomedical Big Data
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    Chapter 6 Semantic Technologies and Bio-Ontologies
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    Chapter 7 Genome-Wide Analysis of MicroRNA-Regulated Transcripts
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    Chapter 8 Computational Prediction of MicroRNA Target Genes, Target Prediction Databases, and Web Resources
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    Chapter 9 Exploring MicroRNA::Target Regulatory Interactions by Computing Technologies
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    Chapter 10 The Limitations of Existing Approaches in Improving MicroRNA Target Prediction Accuracy.
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    Chapter 11 Genomic Regulation of MicroRNA Expression in Disease Development
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    Chapter 12 Next-Generation Sequencing for MicroRNA Expression Profile
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    Chapter 13 Handling High-Dimension (High-Feature) MicroRNA Data.
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    Chapter 14 Effective Removal of Noisy Data Via Batch Effect Processing
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    Chapter 15 Logical Reasoning (Inferencing) on MicroRNA Data
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    Chapter 16 Machine Learning Techniques in Exploring MicroRNA Gene Discovery, Targets, and Functions
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    Chapter 17 Involvement of MicroRNAs in Diabetes and Its Complications
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    Chapter 18 MicroRNA Regulatory Networks as Biomarkers in Obesity: The Emerging Role.
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    Chapter 19 Expression of MicroRNAs in Thyroid Carcinoma.
Attention for Chapter 7: Genome-Wide Analysis of MicroRNA-Regulated Transcripts
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Chapter title
Genome-Wide Analysis of MicroRNA-Regulated Transcripts
Chapter number 7
Book title
Bioinformatics in MicroRNA Research
Published in
Methods in molecular biology, May 2017
DOI 10.1007/978-1-4939-7046-9_7
Pubmed ID
Book ISBNs
978-1-4939-7044-5, 978-1-4939-7046-9
Authors

David Chevalier, Glen M. Borchert Ph.D., Glen M. Borchert

Editors

Jingshan Huang, Glen M. Borchert, Dejing Dou, Jun (Luke) Huan, Wenjun Lan, Ming Tan, Bin Wu

Abstract

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression by either degrading transcripts or repressing translation . Over the past decade the significance of miRNAs has been unraveled by the characterization of their involvement in crucial cellular functions and the development of disease. However, continued progress in understanding the endogenous importance of miRNAs, as well as their potential uses as therapeutic tools, has been hindered by the difficulty of positively identifying miRNA targets. To face this challenge algorithmic approaches have primarily been utilized to date, but strictly mathematical models have thus far failed to produce a generally accurate, widely accepted methodology for accurate miRNA target determination. As such, several laboratory-based, comprehensive strategies for experimentally identifying all cellular miRNA regulations simultaneously have recently been developed. This chapter discusses the advantages and limitations of both classic and comprehensive strategies for miRNA target prediction .

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 29%
Student > Bachelor 1 14%
Student > Doctoral Student 1 14%
Librarian 1 14%
Professor > Associate Professor 1 14%
Other 1 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 29%
Biochemistry, Genetics and Molecular Biology 2 29%
Chemical Engineering 1 14%
Computer Science 1 14%
Psychology 1 14%
Other 0 0%