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KOMODO:一个用于检测和可视化单系分类群中同源基因分组的偏置分布的网络工具。

KOMODO: a web tool for detecting and visualizing biased distribution of groups of homologous genes in monophyletic taxa.

机构信息

Laboratório Multiusuário de Bioinformática, Embrapa Informática Agropecuária, Campinas, São Paulo 13083 886, Brazil.

出版信息

Nucleic Acids Res. 2012 Jul;40(Web Server issue):W491-7. doi: 10.1093/nar/gks490. Epub 2012 Jun 6.

Abstract

The enrichment analysis is a standard procedure to interpret 'omics' experiments that generate large gene lists as outputs, such as transcriptomics and protemics. However, despite the huge success of enrichment analysis in these classes of experiments, there is a surprising lack of application of this methodology to survey other categories of large-scale biological data available. Here, we report Kegg Orthology enrichMent-Online DetectiOn (KOMODO), a web tool to systematically investigate groups of monophyletic genomes in order to detect significantly enriched groups of homologous genes in one taxon when compared with another. The results are displayed in their proper biochemical roles in a visual, explorative way, allowing users to easily formulate and investigate biological hypotheses regarding the taxonomical distribution of genomic elements. We validated KOMODO by analyzing portions of central carbon metabolism in two taxa extensively studied regarding their carbon metabolism profile (Enterobacteriaceae family and Lactobacillales order). Most enzymatic activities significantly biased were related to known key metabolic traits in these taxa, such as the distinct fates of pyruvate (the known tendency of lactate production in Lactobacillales and its complete oxidation in Enterobacteriaceae), demonstrating that KOMODO could detect biologically meaningful differences in the frequencies of shared genomic elements among taxa. KOMODO is freely available at http://komodotool.org.

摘要

富集分析是一种标准的程序,可以解释产生大量基因列表的“组学”实验,如转录组学和蛋白质组学。然而,尽管富集分析在这些实验类别中取得了巨大的成功,但令人惊讶的是,这种方法并没有应用于其他类别的大规模生物数据。在这里,我们报告了 Kegg Orthology enrichMent-Online DetectiOn (KOMODO),这是一个网络工具,用于系统地调查单系基因组的群体,以便在与另一个基因组比较时检测到一个分类群中同源基因的显著富集群体。结果以可视化、探索性的方式显示在其适当的生化作用中,允许用户轻松地制定和调查关于基因组元素的分类分布的生物学假设。我们通过分析两个在其碳代谢特征方面得到广泛研究的分类群(肠杆菌科家族和乳杆菌目)的中心碳代谢的部分内容来验证 KOMODO。大多数显著偏向的酶活性与这些分类群中已知的关键代谢特征有关,例如丙酮酸的不同命运(乳杆菌目中已知的乳酸产生趋势及其在肠杆菌科中的完全氧化),这表明 KOMODO 可以检测到在分类群之间共享基因组元素的频率中存在有生物学意义的差异。KOMODO 可在 http://komodotool.org 免费获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d17/3394310/e1badb61c095/gks490f1.jpg

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