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Computational Biology of Non-Coding RNA

Overview of attention for book
Computational Biology of Non-Coding RNA
Springer New York

Table of Contents

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    Book Overview
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    Chapter 1 ncRNAs in Inflammatory and Infectious Diseases
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    Chapter 2 p73-Governed miRNA Networks: Translating Bioinformatics Approaches to Therapeutic Solutions for Cancer Metastasis
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    Chapter 3 Methods for Annotation and Validation of Circular RNAs from RNAseq Data
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    Chapter 4 Methods to Study Long Noncoding RNA Expression and Dynamics in Zebrafish Using RNA Sequencing
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    Chapter 5 Workflow Development for the Functional Characterization of ncRNAs
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    Chapter 6 ncRNA Editing: Functional Characterization and Computational Resources
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    Chapter 7 Computational Prediction of Functional MicroRNA–mRNA Interactions
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    Chapter 8 Tools for Understanding miRNA–mRNA Interactions for Reproducible RNA Analysis
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    Chapter 9 Computational Resources for Prediction and Analysis of Functional miRNA and Their Targetome
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    Chapter 10 Noncoding RNAs Databases: Current Status and Trends
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    Chapter 11 Controllability Methods for Identifying Associations Between Critical Control ncRNAs and Human Diseases
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    Chapter 12 Network-Based Methods and Other Approaches for Predicting lncRNA Functions and Disease Associations
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    Chapter 13 Integration of miRNA and mRNA Expression Data for Understanding Etiology of Gynecologic Cancers
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    Chapter 14 Quantitative Characteristic of ncRNA Regulation in Gene Regulatory Networks
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    Chapter 15 Kinetic Modelling of Competition and Depletion of Shared miRNAs by Competing Endogenous RNAs
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    Chapter 16 Modeling ncRNA-Mediated Circuits in Cell Fate Decision
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    Chapter 17 Modeling Long ncRNA-Mediated Regulation in the Mammalian Cell Cycle
Attention for Chapter 7: Computational Prediction of Functional MicroRNA–mRNA Interactions
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Chapter title
Computational Prediction of Functional MicroRNA–mRNA Interactions
Chapter number 7
Book title
Computational Biology of Non-Coding RNA
Published by
Humana Press, New York, NY, January 2019
DOI 10.1007/978-1-4939-8982-9_7
Pubmed ID
Book ISBNs
978-1-4939-8981-2, 978-1-4939-8982-9
Authors

Müşerref Duygu Saçar Demirci, Malik Yousef, Jens Allmer, Saçar Demirci, Müşerref Duygu, Yousef, Malik, Allmer, Jens

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 28%
Student > Master 3 12%
Professor > Associate Professor 2 8%
Other 1 4%
Professor 1 4%
Other 3 12%
Unknown 8 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 28%
Computer Science 3 12%
Agricultural and Biological Sciences 2 8%
Medicine and Dentistry 2 8%
Psychology 1 4%
Other 1 4%
Unknown 9 36%