In silico Reconstruction of the Metabolic and Pathogenic Potential of Bacterial Genomes Using Subsystems.

Genome dynamics Pub Date : 2009-01-01 Epub Date: 2009-08-19 DOI:10.1159/000235760
L K McNeil, R K Aziz
{"title":"In silico Reconstruction of the Metabolic and Pathogenic Potential of Bacterial Genomes Using Subsystems.","authors":"L K McNeil,&nbsp;R K Aziz","doi":"10.1159/000235760","DOIUrl":null,"url":null,"abstract":"<p><p>Whole genome sequencing has revolutionized biological sciences, and is leading to a paradigm shift in microbiology. As more microbial genomes are sequenced, and more bioinformatics tools are developed, it has become possible to predict the metabolism of an organism from genomic data. In contrast, predicting the pathogenic potential of parasitic microbes and their interactions with their hosts is still a challenge, especially as the definition of pathogenesis itself is still evolving. In this review, we introduce the subsystem-based technology for genome annotation and analysis, and we discuss some subsystem-based tools available in the National Microbial Pathogen Data Resource (NMPDR, http://www.nmpdr.org) and their potential application in comparative genomics and pathogenomics.</p>","PeriodicalId":87974,"journal":{"name":"Genome dynamics","volume":"6 ","pages":"21-34"},"PeriodicalIF":0.0000,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000235760","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genome dynamics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1159/000235760","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2009/8/19 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Whole genome sequencing has revolutionized biological sciences, and is leading to a paradigm shift in microbiology. As more microbial genomes are sequenced, and more bioinformatics tools are developed, it has become possible to predict the metabolism of an organism from genomic data. In contrast, predicting the pathogenic potential of parasitic microbes and their interactions with their hosts is still a challenge, especially as the definition of pathogenesis itself is still evolving. In this review, we introduce the subsystem-based technology for genome annotation and analysis, and we discuss some subsystem-based tools available in the National Microbial Pathogen Data Resource (NMPDR, http://www.nmpdr.org) and their potential application in comparative genomics and pathogenomics.

利用子系统对细菌基因组的代谢和致病潜能进行计算机重建。
全基因组测序已经彻底改变了生物科学,并导致了微生物学范式的转变。随着越来越多的微生物基因组测序和越来越多的生物信息学工具的开发,从基因组数据预测生物体的代谢已经成为可能。相比之下,预测寄生微生物的致病潜力及其与宿主的相互作用仍然是一个挑战,特别是在发病机制本身的定义仍在不断发展的情况下。本文介绍了基于子系统的基因组注释和分析技术,并讨论了国家微生物病原体数据资源(NMPDR, http://www.nmpdr.org)中一些基于子系统的工具及其在比较基因组学和病理基因组学中的潜在应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信