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
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% |