In silico target-specific siRNA design based on domain transfer in heterogeneous data.

RNA interference via exogenous small interference RNAs (siRNA) is a powerful tool in gene function study and disease treatment. Designing efficient and specific siRNA on target gene remains the key issue in RNAi. Although various in silico models have been proposed for rational siRNA design, most of...

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Autores principales:	Qi Liu, Han Zhou, Kui Zhang, Xiaoxiao Shi, Wei Fan, Ruixin Zhu, Philip S Yu, Zhiwei Cao
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ac4646e23acf431cbf8fbfe95f0d2405
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spelling	oai:doaj.org-article:ac4646e23acf431cbf8fbfe95f0d24052021-11-18T08:04:00ZIn silico target-specific siRNA design based on domain transfer in heterogeneous data.1932-620310.1371/journal.pone.0050697https://doaj.org/article/ac4646e23acf431cbf8fbfe95f0d24052012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23284642/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203RNA interference via exogenous small interference RNAs (siRNA) is a powerful tool in gene function study and disease treatment. Designing efficient and specific siRNA on target gene remains the key issue in RNAi. Although various in silico models have been proposed for rational siRNA design, most of them focus on the efficiencies of selected siRNAs, while limited effort has been made to improve their specificities targeted on specific mRNAs, which is related to reducing off-target effects (OTEs) in RNAi. In our study, we propose for the first time that the enhancement of target specificity of siRNA design can be achieved computationally by domain transfer in heterogeneous data sources from different siRNA targets. A transfer learning based method i.e., heterogeneous regression (HEGS) is presented for target-specific siRNA efficacy modeling and feature selection. Based on the model, (1) the target regression model can be built by extracting information from related data in other targets/experiments, thus increasing the target specificity in siRNA design with the help of information from siRNAs binding to other homologous genes, and (2) the potential features correlated to the current siRNA design can be identified even when there is lack of experimental validated siRNA affinity data on this target. In summary, our findings present useful instructions for a better target-specific siRNA design, with potential applications in genome-wide high-throughput screening of effective siRNA, and will provide further insights on the mechanism of RNAi.Qi LiuHan ZhouKui ZhangXiaoxiao ShiWei FanRuixin ZhuPhilip S YuZhiwei CaoPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 12, p e50697 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Qi Liu Han Zhou Kui Zhang Xiaoxiao Shi Wei Fan Ruixin Zhu Philip S Yu Zhiwei Cao In silico target-specific siRNA design based on domain transfer in heterogeneous data.
description	RNA interference via exogenous small interference RNAs (siRNA) is a powerful tool in gene function study and disease treatment. Designing efficient and specific siRNA on target gene remains the key issue in RNAi. Although various in silico models have been proposed for rational siRNA design, most of them focus on the efficiencies of selected siRNAs, while limited effort has been made to improve their specificities targeted on specific mRNAs, which is related to reducing off-target effects (OTEs) in RNAi. In our study, we propose for the first time that the enhancement of target specificity of siRNA design can be achieved computationally by domain transfer in heterogeneous data sources from different siRNA targets. A transfer learning based method i.e., heterogeneous regression (HEGS) is presented for target-specific siRNA efficacy modeling and feature selection. Based on the model, (1) the target regression model can be built by extracting information from related data in other targets/experiments, thus increasing the target specificity in siRNA design with the help of information from siRNAs binding to other homologous genes, and (2) the potential features correlated to the current siRNA design can be identified even when there is lack of experimental validated siRNA affinity data on this target. In summary, our findings present useful instructions for a better target-specific siRNA design, with potential applications in genome-wide high-throughput screening of effective siRNA, and will provide further insights on the mechanism of RNAi.
format	article
author	Qi Liu Han Zhou Kui Zhang Xiaoxiao Shi Wei Fan Ruixin Zhu Philip S Yu Zhiwei Cao
author_facet	Qi Liu Han Zhou Kui Zhang Xiaoxiao Shi Wei Fan Ruixin Zhu Philip S Yu Zhiwei Cao
author_sort	Qi Liu
title	In silico target-specific siRNA design based on domain transfer in heterogeneous data.
title_short	In silico target-specific siRNA design based on domain transfer in heterogeneous data.
title_full	In silico target-specific siRNA design based on domain transfer in heterogeneous data.
title_fullStr	In silico target-specific siRNA design based on domain transfer in heterogeneous data.
title_full_unstemmed	In silico target-specific siRNA design based on domain transfer in heterogeneous data.
title_sort	in silico target-specific sirna design based on domain transfer in heterogeneous data.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/ac4646e23acf431cbf8fbfe95f0d2405
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In silico target-specific siRNA design based on domain transfer in heterogeneous data.

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