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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
  2. Altmetric Badge
    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 8: Computational Prediction of MicroRNA Target Genes, Target Prediction Databases, and Web Resources
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Chapter title
Computational Prediction of MicroRNA Target Genes, Target Prediction Databases, and Web Resources
Chapter number 8
Book title
Bioinformatics in MicroRNA Research
Published in
Methods in molecular biology, May 2017
DOI 10.1007/978-1-4939-7046-9_8
Pubmed ID
Book ISBNs
978-1-4939-7044-5, 978-1-4939-7046-9
Authors

Justin T. Roberts, 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

MicroRNA (miRNA) mediated silencing and repression of mRNA molecules requires complementary base pairing between the "seed" region of the miRNA and the "seed match" region of target mRNAs. While this mechanism is fairly well understood, accurate prediction of valid miRNA targets remains challenging due to factors such as imperfect sequence specificity, target site availability, and the thermodynamic stability of the mRNA structure itself. As knowledge of what genes are being targeted by each miRNA is arguably the most important facet of miRNA biology, many approaches have been developed to address the need for reliable prediction and ranking of putative targets, with most using a combination of various strategies such as evolutionary conservation, statistical inference, and distinct features of the target sequences themselves. This chapter reviews the pros and cons of a number of different prediction algorithms, showcases some databases that store experimentally validated miRNA targets, and also provides a case study that profiles some of the potential microRNA-mRNA interactions predicted by each methodology for various human genes.

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 25%
Student > Doctoral Student 3 15%
Student > Master 3 15%
Student > Bachelor 3 15%
Researcher 3 15%
Other 2 10%
Unknown 1 5%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 40%
Computer Science 3 15%
Agricultural and Biological Sciences 2 10%
Chemical Engineering 1 5%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Other 4 20%
Unknown 1 5%