创新microRNA-lncRNA-mRNA共表达分析,了解糖尿病肾病的发病和进展

Lihua Zhang, Rong Li, Qiuping Yang, Yanan Wu, Jingshan Huang, Bin Wu
{"title":"创新microRNA-lncRNA-mRNA共表达分析,了解糖尿病肾病的发病和进展","authors":"Lihua Zhang, Rong Li, Qiuping Yang, Yanan Wu, Jingshan Huang, Bin Wu","doi":"10.1109/BIBM.2016.7822601","DOIUrl":null,"url":null,"abstract":"Diabetic kidney disease (DKD) is a serious disease that presents a major health problem worldwide. There is a desperate need to explore novel biomarkers to further facilitate the early diagnosis and effective treatment in DKD patients so that to prevent them to develop end-stage renal disease (ESRD). However, most of regulation mechanisms at genetic level in DKD still remain unclear. In this work-in-progress paper, we describe our innovative methodologies that integrate biological, statistics, and computational approaches to investigate important roles performed by regulations among microRNAs (miRs), long non-coding RNAs (lncRNAs), and messenger RNAs (mRNAs) in DKD. We conducted a series of experiments and identified a list of miRs and lncRNAs as potential novel biomarkers, along with the set of target genes regulated by discovered miRs. Our initial analysis results are promising in better understanding regulation mechanisms of miRs and lncRNAs on the pathogenesis and progression of DKD.","PeriodicalId":345384,"journal":{"name":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Innovative microRNA-lncRNA-mRNA co-expression analysis to understand the pathogenesis and progression of diabetic kidney disease\",\"authors\":\"Lihua Zhang, Rong Li, Qiuping Yang, Yanan Wu, Jingshan Huang, Bin Wu\",\"doi\":\"10.1109/BIBM.2016.7822601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Diabetic kidney disease (DKD) is a serious disease that presents a major health problem worldwide. There is a desperate need to explore novel biomarkers to further facilitate the early diagnosis and effective treatment in DKD patients so that to prevent them to develop end-stage renal disease (ESRD). However, most of regulation mechanisms at genetic level in DKD still remain unclear. In this work-in-progress paper, we describe our innovative methodologies that integrate biological, statistics, and computational approaches to investigate important roles performed by regulations among microRNAs (miRs), long non-coding RNAs (lncRNAs), and messenger RNAs (mRNAs) in DKD. We conducted a series of experiments and identified a list of miRs and lncRNAs as potential novel biomarkers, along with the set of target genes regulated by discovered miRs. Our initial analysis results are promising in better understanding regulation mechanisms of miRs and lncRNAs on the pathogenesis and progression of DKD.\",\"PeriodicalId\":345384,\"journal\":{\"name\":\"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBM.2016.7822601\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2016.7822601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

糖尿病肾病(DKD)是一种严重的疾病,是世界范围内的主要健康问题。迫切需要探索新的生物标志物,进一步促进DKD患者的早期诊断和有效治疗,以防止其发展为终末期肾脏疾病(ESRD)。然而,DKD在遗传水平上的调控机制仍不清楚。在这篇正在进行的论文中,我们描述了我们的创新方法,该方法整合了生物学,统计学和计算方法,以研究microRNAs (miRs),长链非编码rna (lncRNAs)和信使rna (mrna)之间的调控在DKD中发挥的重要作用。我们进行了一系列实验,并确定了一系列miRs和lncrna作为潜在的新型生物标志物,以及一组由发现的miRs调控的靶基因。我们的初步分析结果有望更好地理解miRs和lncrna对DKD发病和进展的调控机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Innovative microRNA-lncRNA-mRNA co-expression analysis to understand the pathogenesis and progression of diabetic kidney disease
Diabetic kidney disease (DKD) is a serious disease that presents a major health problem worldwide. There is a desperate need to explore novel biomarkers to further facilitate the early diagnosis and effective treatment in DKD patients so that to prevent them to develop end-stage renal disease (ESRD). However, most of regulation mechanisms at genetic level in DKD still remain unclear. In this work-in-progress paper, we describe our innovative methodologies that integrate biological, statistics, and computational approaches to investigate important roles performed by regulations among microRNAs (miRs), long non-coding RNAs (lncRNAs), and messenger RNAs (mRNAs) in DKD. We conducted a series of experiments and identified a list of miRs and lncRNAs as potential novel biomarkers, along with the set of target genes regulated by discovered miRs. Our initial analysis results are promising in better understanding regulation mechanisms of miRs and lncRNAs on the pathogenesis and progression of DKD.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The role of high performance, grid and cloud computing in high-throughput sequencing A novel algorithm for identifying essential proteins by integrating subcellular localization CNNsite: Prediction of DNA-binding residues in proteins using Convolutional Neural Network with sequence features Inferring Social Influence of anti-Tobacco mass media campaigns Emotion recognition from multi-channel EEG data through Convolutional Recurrent Neural Network
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1