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Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets

Identifying the occurrence mechanism of drug-induced side effects (SEs) is critical for design of drug target and new drug development. The expression of genes in biological processes is regulated by transcription factors(TFs) and/or microRNAs. Most of previous studies were focused on a single level...

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Autores principales: Jia, Xiaodong, Jin, Qing, Liu, Xiangqiong, Bian, Xiusen, Wang, Yunfeng, Liu, Lei, Ma, Hongzhe, Tan, Fujian, Gu, Mingliang, Chen, Xiujie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519677/
https://www.ncbi.nlm.nih.gov/pubmed/28729650
http://dx.doi.org/10.1038/s41598-017-06083-5
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author Jia, Xiaodong
Jin, Qing
Liu, Xiangqiong
Bian, Xiusen
Wang, Yunfeng
Liu, Lei
Ma, Hongzhe
Tan, Fujian
Gu, Mingliang
Chen, Xiujie
author_facet Jia, Xiaodong
Jin, Qing
Liu, Xiangqiong
Bian, Xiusen
Wang, Yunfeng
Liu, Lei
Ma, Hongzhe
Tan, Fujian
Gu, Mingliang
Chen, Xiujie
author_sort Jia, Xiaodong
collection PubMed
description Identifying the occurrence mechanism of drug-induced side effects (SEs) is critical for design of drug target and new drug development. The expression of genes in biological processes is regulated by transcription factors(TFs) and/or microRNAs. Most of previous studies were focused on a single level of gene or gene sets, while studies about regulatory relationships of TFs, miRNAs and biological processes are very rare. Discovering the complex regulating relations among TFs, gene sets and miRNAs will be helpful for researchers to get a more comprehensive understanding about the mechanism of side reaction. In this study, a framework was proposed to construct the relationship network of gene sets, miRNAs and TFs involved in side effects. Through the construction of this network, the potential complex regulatory relationship in the occurrence process of the side effects was reproduced. The SE-gene set network was employed to characterize the significant regulatory SE-gene set interaction and molecular basis of accompanied side effects. A total of 117 side effects complex modules including four types of regulating patterns were obtained from the SE-gene sets-miRNA/TF complex regulatory network. In addition, two cases were used to validate the complex regulatory modules which could more comprehensively interpret occurrence mechanism of side effects.
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spelling pubmed-55196772017-07-21 Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets Jia, Xiaodong Jin, Qing Liu, Xiangqiong Bian, Xiusen Wang, Yunfeng Liu, Lei Ma, Hongzhe Tan, Fujian Gu, Mingliang Chen, Xiujie Sci Rep Article Identifying the occurrence mechanism of drug-induced side effects (SEs) is critical for design of drug target and new drug development. The expression of genes in biological processes is regulated by transcription factors(TFs) and/or microRNAs. Most of previous studies were focused on a single level of gene or gene sets, while studies about regulatory relationships of TFs, miRNAs and biological processes are very rare. Discovering the complex regulating relations among TFs, gene sets and miRNAs will be helpful for researchers to get a more comprehensive understanding about the mechanism of side reaction. In this study, a framework was proposed to construct the relationship network of gene sets, miRNAs and TFs involved in side effects. Through the construction of this network, the potential complex regulatory relationship in the occurrence process of the side effects was reproduced. The SE-gene set network was employed to characterize the significant regulatory SE-gene set interaction and molecular basis of accompanied side effects. A total of 117 side effects complex modules including four types of regulating patterns were obtained from the SE-gene sets-miRNA/TF complex regulatory network. In addition, two cases were used to validate the complex regulatory modules which could more comprehensively interpret occurrence mechanism of side effects. Nature Publishing Group UK 2017-07-20 /pmc/articles/PMC5519677/ /pubmed/28729650 http://dx.doi.org/10.1038/s41598-017-06083-5 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Jia, Xiaodong
Jin, Qing
Liu, Xiangqiong
Bian, Xiusen
Wang, Yunfeng
Liu, Lei
Ma, Hongzhe
Tan, Fujian
Gu, Mingliang
Chen, Xiujie
Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
title Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
title_full Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
title_fullStr Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
title_full_unstemmed Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
title_short Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
title_sort large-scale analysis of drug side effects via complex regulatory modules composed of micrornas, transcription factors and gene sets
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519677/
https://www.ncbi.nlm.nih.gov/pubmed/28729650
http://dx.doi.org/10.1038/s41598-017-06083-5
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