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Psmir: a database of potential associations between small molecules and miRNAs

miRNAs are key post-transcriptional regulators of many essential biological processes, and their dysregulation has been validated in almost all human cancers. Restoring aberrantly expressed miRNAs might be a novel therapeutics. Recently, many studies have demonstrated that small molecular compounds...

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Autores principales: Meng, Fanlin, Wang, Jing, Dai, Enyu, Yang, Feng, Chen, Xiaowen, Wang, Shuyuan, Yu, Xuexin, Liu, Dianming, Jiang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4713048/
https://www.ncbi.nlm.nih.gov/pubmed/26759061
http://dx.doi.org/10.1038/srep19264
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author Meng, Fanlin
Wang, Jing
Dai, Enyu
Yang, Feng
Chen, Xiaowen
Wang, Shuyuan
Yu, Xuexin
Liu, Dianming
Jiang, Wei
author_facet Meng, Fanlin
Wang, Jing
Dai, Enyu
Yang, Feng
Chen, Xiaowen
Wang, Shuyuan
Yu, Xuexin
Liu, Dianming
Jiang, Wei
author_sort Meng, Fanlin
collection PubMed
description miRNAs are key post-transcriptional regulators of many essential biological processes, and their dysregulation has been validated in almost all human cancers. Restoring aberrantly expressed miRNAs might be a novel therapeutics. Recently, many studies have demonstrated that small molecular compounds can affect miRNA expression. Thus, prediction of associations between small molecules and miRNAs is important for investigation of miRNA-targeted drugs. Here, we analyzed 39 miRNA-perturbed gene expression profiles, and then calculated the similarity of transcription responses between miRNA perturbation and drug treatment to predict drug-miRNA associations. At the significance level of 0.05, we obtained 6501 candidate associations between 1295 small molecules and 25 miRNAs, which included 624 FDA approved drugs. Finally, we constructed the Psmir database to store all potential associations and the related materials. In a word, Psmir served as a valuable resource for dissecting the biological significance in small molecules’ effects on miRNA expression, which will facilitate developing novel potential therapeutic targets or treatments for human cancers. Psmir is supported by all major browsers, and is freely available at http://www.bio-bigdata.com/Psmir/.
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spelling pubmed-47130482016-01-20 Psmir: a database of potential associations between small molecules and miRNAs Meng, Fanlin Wang, Jing Dai, Enyu Yang, Feng Chen, Xiaowen Wang, Shuyuan Yu, Xuexin Liu, Dianming Jiang, Wei Sci Rep Article miRNAs are key post-transcriptional regulators of many essential biological processes, and their dysregulation has been validated in almost all human cancers. Restoring aberrantly expressed miRNAs might be a novel therapeutics. Recently, many studies have demonstrated that small molecular compounds can affect miRNA expression. Thus, prediction of associations between small molecules and miRNAs is important for investigation of miRNA-targeted drugs. Here, we analyzed 39 miRNA-perturbed gene expression profiles, and then calculated the similarity of transcription responses between miRNA perturbation and drug treatment to predict drug-miRNA associations. At the significance level of 0.05, we obtained 6501 candidate associations between 1295 small molecules and 25 miRNAs, which included 624 FDA approved drugs. Finally, we constructed the Psmir database to store all potential associations and the related materials. In a word, Psmir served as a valuable resource for dissecting the biological significance in small molecules’ effects on miRNA expression, which will facilitate developing novel potential therapeutic targets or treatments for human cancers. Psmir is supported by all major browsers, and is freely available at http://www.bio-bigdata.com/Psmir/. Nature Publishing Group 2016-01-13 /pmc/articles/PMC4713048/ /pubmed/26759061 http://dx.doi.org/10.1038/srep19264 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Meng, Fanlin
Wang, Jing
Dai, Enyu
Yang, Feng
Chen, Xiaowen
Wang, Shuyuan
Yu, Xuexin
Liu, Dianming
Jiang, Wei
Psmir: a database of potential associations between small molecules and miRNAs
title Psmir: a database of potential associations between small molecules and miRNAs
title_full Psmir: a database of potential associations between small molecules and miRNAs
title_fullStr Psmir: a database of potential associations between small molecules and miRNAs
title_full_unstemmed Psmir: a database of potential associations between small molecules and miRNAs
title_short Psmir: a database of potential associations between small molecules and miRNAs
title_sort psmir: a database of potential associations between small molecules and mirnas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4713048/
https://www.ncbi.nlm.nih.gov/pubmed/26759061
http://dx.doi.org/10.1038/srep19264
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