Revealing protein–lncRNA interaction
Long non-coding RNAs (lncRNAs) are associated to a plethora of cellular functions, most of which require the interaction with one or more RNA-binding proteins (RBPs); similarly, RBPs are often able to bind a large number of different RNAs. The currently available knowledge is already drawing an intr...
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| Format: | Online |
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Oxford University Press
2016
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4719072/ |
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pubmed-47190722016-01-21 Revealing protein–lncRNA interaction Ferrè, Fabrizio Colantoni, Alessio Helmer-Citterich, Manuela Papers Long non-coding RNAs (lncRNAs) are associated to a plethora of cellular functions, most of which require the interaction with one or more RNA-binding proteins (RBPs); similarly, RBPs are often able to bind a large number of different RNAs. The currently available knowledge is already drawing an intricate network of interactions, whose deregulation is frequently associated to pathological states. Several different techniques were developed in the past years to obtain protein–RNA binding data in a high-throughput fashion. In parallel, in silico inference methods were developed for the accurate computational prediction of the interaction of RBP–lncRNA pairs. The field is growing rapidly, and it is foreseeable that in the near future, the protein–lncRNA interaction network will rise, offering essential clues for a better understanding of lncRNA cellular mechanisms and their disease-associated perturbations. Oxford University Press 2016-01 2015-06-02 /pmc/articles/PMC4719072/ /pubmed/26041786 http://dx.doi.org/10.1093/bib/bbv031 Text en © The Author 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Ferrè, Fabrizio Colantoni, Alessio Helmer-Citterich, Manuela |
| spellingShingle |
Ferrè, Fabrizio Colantoni, Alessio Helmer-Citterich, Manuela Revealing protein–lncRNA interaction |
| author_facet |
Ferrè, Fabrizio Colantoni, Alessio Helmer-Citterich, Manuela |
| author_sort |
Ferrè, Fabrizio |
| title |
Revealing protein–lncRNA interaction |
| title_short |
Revealing protein–lncRNA interaction |
| title_full |
Revealing protein–lncRNA interaction |
| title_fullStr |
Revealing protein–lncRNA interaction |
| title_full_unstemmed |
Revealing protein–lncRNA interaction |
| title_sort |
revealing protein–lncrna interaction |
| description |
Long non-coding RNAs (lncRNAs) are associated to a plethora of cellular functions, most of which require the interaction with one or more RNA-binding proteins (RBPs); similarly, RBPs are often able to bind a large number of different RNAs. The currently available knowledge is already drawing an intricate network of interactions, whose deregulation is frequently associated to pathological states. Several different techniques were developed in the past years to obtain protein–RNA binding data in a high-throughput fashion. In parallel, in silico inference methods were developed for the accurate computational prediction of the interaction of RBP–lncRNA pairs. The field is growing rapidly, and it is foreseeable that in the near future, the protein–lncRNA interaction network will rise, offering essential clues for a better understanding of lncRNA cellular mechanisms and their disease-associated perturbations. |
| publisher |
Oxford University Press |
| publishDate |
2016 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4719072/ |
| _version_ |
1613525921860419584 |