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Genetic studies of diseases: Predicting siRNA efficiency
Since the identification of RNA-mediated interference (RNAi) in 1998, RNAi has become an effective tool to inhibit gene expression. The inhibition mechanism is triggered by introducing a short interference double-stranded RNA (siRNA,19~27 bp) into the cytoplasm, where the guide strand of siRNA (usua...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Birkhäuser-Verlag
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079790/ https://www.ncbi.nlm.nih.gov/pubmed/17415516 http://dx.doi.org/10.1007/s00018-007-7057-3 |
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author | Li, W. Cha, L. |
author_facet | Li, W. Cha, L. |
author_sort | Li, W. |
collection | PubMed |
description | Since the identification of RNA-mediated interference (RNAi) in 1998, RNAi has become an effective tool to inhibit gene expression. The inhibition mechanism is triggered by introducing a short interference double-stranded RNA (siRNA,19~27 bp) into the cytoplasm, where the guide strand of siRNA (usually antisense strand) binds to its target messenger RNA and the expression of the target gene is blocked. RNAi has been widely applied in gene functional analysis, and as a potential therapeutic strategy in viral diseases, drug target discovery, and cancer therapy. Among the factors which may compromise inhibition efficiency, how to design siRNAs with high efficiency and high specificity to its target gene is critical. Although many algorithms have been developed for this purpose, it is still difficult to design such siRNAs. In this review, we will briefly discuss prediction methods for siRNA efficiency and the problems of present approaches. |
format | Online Article Text |
id | pubmed-7079790 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Birkhäuser-Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-70797902020-03-23 Genetic studies of diseases: Predicting siRNA efficiency Li, W. Cha, L. Cell Mol Life Sci Multi-author Review Since the identification of RNA-mediated interference (RNAi) in 1998, RNAi has become an effective tool to inhibit gene expression. The inhibition mechanism is triggered by introducing a short interference double-stranded RNA (siRNA,19~27 bp) into the cytoplasm, where the guide strand of siRNA (usually antisense strand) binds to its target messenger RNA and the expression of the target gene is blocked. RNAi has been widely applied in gene functional analysis, and as a potential therapeutic strategy in viral diseases, drug target discovery, and cancer therapy. Among the factors which may compromise inhibition efficiency, how to design siRNAs with high efficiency and high specificity to its target gene is critical. Although many algorithms have been developed for this purpose, it is still difficult to design such siRNAs. In this review, we will briefly discuss prediction methods for siRNA efficiency and the problems of present approaches. Birkhäuser-Verlag 2007-04-06 2007 /pmc/articles/PMC7079790/ /pubmed/17415516 http://dx.doi.org/10.1007/s00018-007-7057-3 Text en © Birkhäuser Verlag, Basel 2007 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Multi-author Review Li, W. Cha, L. Genetic studies of diseases: Predicting siRNA efficiency |
title | Genetic studies of diseases: Predicting siRNA efficiency |
title_full | Genetic studies of diseases: Predicting siRNA efficiency |
title_fullStr | Genetic studies of diseases: Predicting siRNA efficiency |
title_full_unstemmed | Genetic studies of diseases: Predicting siRNA efficiency |
title_short | Genetic studies of diseases: Predicting siRNA efficiency |
title_sort | genetic studies of diseases: predicting sirna efficiency |
topic | Multi-author Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079790/ https://www.ncbi.nlm.nih.gov/pubmed/17415516 http://dx.doi.org/10.1007/s00018-007-7057-3 |
work_keys_str_mv | AT liw geneticstudiesofdiseasespredictingsirnaefficiency AT chal geneticstudiesofdiseasespredictingsirnaefficiency |