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Predicting sRNAs and Their Targets in Bacteria
Bacterial small RNAs (sRNAs) are an emerging class of regulatory RNAs of about 40–500 nucleotides in length and, by binding to their target mRNAs or proteins, get involved in many biological processes such as sensing environmental changes and regulating gene expression. Thus, identification of bacte...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054197/ https://www.ncbi.nlm.nih.gov/pubmed/23200137 http://dx.doi.org/10.1016/j.gpb.2012.09.004 |
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author | Li, Wuju Ying, Xiaomin Lu, Qixuan Chen, Linxi |
author_facet | Li, Wuju Ying, Xiaomin Lu, Qixuan Chen, Linxi |
author_sort | Li, Wuju |
collection | PubMed |
description | Bacterial small RNAs (sRNAs) are an emerging class of regulatory RNAs of about 40–500 nucleotides in length and, by binding to their target mRNAs or proteins, get involved in many biological processes such as sensing environmental changes and regulating gene expression. Thus, identification of bacterial sRNAs and their targets has become an important part of sRNA biology. Current strategies for discovery of sRNAs and their targets usually involve bioinformatics prediction followed by experimental validation, emphasizing a key role for bioinformatics prediction. Here, therefore, we provided an overview on prediction methods, focusing on the merits and limitations of each class of models. Finally, we will present our thinking on developing related bioinformatics models in future. |
format | Online Article Text |
id | pubmed-5054197 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-50541972016-10-14 Predicting sRNAs and Their Targets in Bacteria Li, Wuju Ying, Xiaomin Lu, Qixuan Chen, Linxi Genomics Proteomics Bioinformatics Review Bacterial small RNAs (sRNAs) are an emerging class of regulatory RNAs of about 40–500 nucleotides in length and, by binding to their target mRNAs or proteins, get involved in many biological processes such as sensing environmental changes and regulating gene expression. Thus, identification of bacterial sRNAs and their targets has become an important part of sRNA biology. Current strategies for discovery of sRNAs and their targets usually involve bioinformatics prediction followed by experimental validation, emphasizing a key role for bioinformatics prediction. Here, therefore, we provided an overview on prediction methods, focusing on the merits and limitations of each class of models. Finally, we will present our thinking on developing related bioinformatics models in future. Elsevier 2012-10 2012-10-22 /pmc/articles/PMC5054197/ /pubmed/23200137 http://dx.doi.org/10.1016/j.gpb.2012.09.004 Text en © 2012 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China. Published by Elsevier Ltd and Science Press. All rights reserved. http://creativecommons.org/licenses/by-nc-sa/3.0/ This is an open access article under the CC BY-NC-SA license (http://creativecommons.org/licenses/by-nc-sa/3.0/). |
spellingShingle | Review Li, Wuju Ying, Xiaomin Lu, Qixuan Chen, Linxi Predicting sRNAs and Their Targets in Bacteria |
title | Predicting sRNAs and Their Targets in Bacteria |
title_full | Predicting sRNAs and Their Targets in Bacteria |
title_fullStr | Predicting sRNAs and Their Targets in Bacteria |
title_full_unstemmed | Predicting sRNAs and Their Targets in Bacteria |
title_short | Predicting sRNAs and Their Targets in Bacteria |
title_sort | predicting srnas and their targets in bacteria |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054197/ https://www.ncbi.nlm.nih.gov/pubmed/23200137 http://dx.doi.org/10.1016/j.gpb.2012.09.004 |
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