↓ Skip to main content

Non-coding RNAs in Complex Diseases

Overview of attention for book
Attention for Chapter 12: Methods for Identification of Protein-RNA Interaction
Altmetric Badge

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
9 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Methods for Identification of Protein-RNA Interaction
Chapter number 12
Book title
Non-coding RNAs in Complex Diseases
Published in
Advances in experimental medicine and biology, September 2018
DOI 10.1007/978-981-13-0719-5_12
Pubmed ID
Book ISBNs
978-9-81-130718-8, 978-9-81-130719-5
Authors

Juan Xu, Zishan Wang, Xiyun Jin, Lili Li, Tao Pan, Xu, Juan, Wang, Zishan, Jin, Xiyun, Li, Lili, Pan, Tao

Abstract

The importance of RNA-protein interactions in regulation of mRNA and non-coding RNA function is increasingly appreciated. With the development of next generation high-throughput sequencing technologies, a variety of methods have been proposed to comprehensively identify RNA-protein interactions. In this chapter, we discussed the traditional and state-of-the-art technologies that were used to study RNA-protein interaction, including experimental and computational methods. To help highlight the biological significance of RNA-protein interaction in complex diseases, online resources on RNA-protein interactions were briefly discussed. Finally, we discussed the interaction among noncoding RNAs (such as long noncoding RNAs and microRNAs) and proteins, as well as the dysregulation of RNA-protein interaction in complex diseases. These summarization will ultimately provide a more complete picture for understanding of the function of RNA-protein interactions, including how these interaction assembled and how they modulate cellular function in complex diseases.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 22%
Student > Ph. D. Student 2 22%
Other 1 11%
Researcher 1 11%
Student > Postgraduate 1 11%
Other 0 0%
Unknown 2 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 44%
Computer Science 1 11%
Agricultural and Biological Sciences 1 11%
Unknown 3 33%