基于基因本体和16S rRNA基因的微生物群落功能分析集成策略

IF 0.2 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY International Journal of Data Mining and Bioinformatics Pub Date : 2015-07-01 DOI:10.1504/IJDMB.2015.070841
Suping Deng, De-shuang Huang
{"title":"基于基因本体和16S rRNA基因的微生物群落功能分析集成策略","authors":"Suping Deng, De-shuang Huang","doi":"10.1504/IJDMB.2015.070841","DOIUrl":null,"url":null,"abstract":"In order to analyse the similarity among microbial communities on functional state after assigning 16S rRNA sequences from all microbial communities to species. It's an important addition to the species-level relationship between two compared communities and can quantify their differences in function. We downloaded all functional annotation data of several microbiotas. It's developed to identify the functional distribution and the significantly enriched functional categories of microbial communities. We analysed the similarity between two microbial communities on functional state. In the experimental results, it shows that the semantic similarity can quantify the difference between two compared species on function level. It can analyse the function of microbial communities by gene ontology based on 16S rRNA gene. Exploration of the function relationship between two sets of species assemblages will be a key result of microbiome studies and may provide new insights into assembly of a wide range of ecosystems.","PeriodicalId":54964,"journal":{"name":"International Journal of Data Mining and Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.2000,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJDMB.2015.070841","citationCount":"4","resultStr":"{\"title\":\"An integrated strategy for functional analysis of microbial communities based on gene ontology and 16S rRNA gene\",\"authors\":\"Suping Deng, De-shuang Huang\",\"doi\":\"10.1504/IJDMB.2015.070841\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to analyse the similarity among microbial communities on functional state after assigning 16S rRNA sequences from all microbial communities to species. It's an important addition to the species-level relationship between two compared communities and can quantify their differences in function. We downloaded all functional annotation data of several microbiotas. It's developed to identify the functional distribution and the significantly enriched functional categories of microbial communities. We analysed the similarity between two microbial communities on functional state. In the experimental results, it shows that the semantic similarity can quantify the difference between two compared species on function level. It can analyse the function of microbial communities by gene ontology based on 16S rRNA gene. Exploration of the function relationship between two sets of species assemblages will be a key result of microbiome studies and may provide new insights into assembly of a wide range of ecosystems.\",\"PeriodicalId\":54964,\"journal\":{\"name\":\"International Journal of Data Mining and Bioinformatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2015-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1504/IJDMB.2015.070841\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Data Mining and Bioinformatics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1504/IJDMB.2015.070841\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Data Mining and Bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1504/IJDMB.2015.070841","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 4

摘要

将所有微生物群落的16S rRNA序列分配给物种后,分析微生物群落在功能状态上的相似性。这是两个比较群落之间物种水平关系的重要补充,可以量化它们在功能上的差异。我们下载了几种微生物群的所有功能注释数据。它的发展是为了确定微生物群落的功能分布和显著丰富的功能类别。我们分析了两个微生物群落在功能状态上的相似性。实验结果表明,语义相似度可以量化两个比较物种在功能水平上的差异。基于16S rRNA基因的基因本体可以分析微生物群落的功能。探索两组物种组合之间的功能关系将是微生物组研究的关键成果,并可能为广泛的生态系统组合提供新的见解。
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
An integrated strategy for functional analysis of microbial communities based on gene ontology and 16S rRNA gene
In order to analyse the similarity among microbial communities on functional state after assigning 16S rRNA sequences from all microbial communities to species. It's an important addition to the species-level relationship between two compared communities and can quantify their differences in function. We downloaded all functional annotation data of several microbiotas. It's developed to identify the functional distribution and the significantly enriched functional categories of microbial communities. We analysed the similarity between two microbial communities on functional state. In the experimental results, it shows that the semantic similarity can quantify the difference between two compared species on function level. It can analyse the function of microbial communities by gene ontology based on 16S rRNA gene. Exploration of the function relationship between two sets of species assemblages will be a key result of microbiome studies and may provide new insights into assembly of a wide range of ecosystems.
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
CiteScore
1.00
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: Mining bioinformatics data is an emerging area at the intersection between bioinformatics and data mining. The objective of IJDMB is to facilitate collaboration between data mining researchers and bioinformaticians by presenting cutting edge research topics and methodologies in the area of data mining for bioinformatics. This perspective acknowledges the inter-disciplinary nature of research in data mining and bioinformatics and provides a unified forum for researchers/practitioners/students/policy makers to share the latest research and developments in this fast growing multi-disciplinary research area.
期刊最新文献
Data mining based integration method of infant critical and critical information in modern hospital Fast retrieval method of biomedical literature based on feature mining Research on Cloud Storage Biological Data De duplication Method Based on Simhash Algorithm Identification of disease-related miRNAs based on Weighted K-Nearest Known Neighbors and Inductive Matrix Completion Diagnosis of Parkinson’s disease genes using LSTM and MLP based multi-feature extraction methods
×
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