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从. 的基因共表达网络中提取信息

Extracting Information from Gene Coexpression Networks of .

机构信息

Department of Statistics, University of Oxford, Oxford, United Kingdom.

Department of Plant Sciences, University of Oxford, Oxford, United Kingdom.

出版信息

J Comput Biol. 2022 Jul;29(7):752-768. doi: 10.1089/cmb.2021.0600. Epub 2022 May 19.

Abstract

Nitrogen uptake in legumes is facilitated by bacteria such as . For this bacterium, gene expression data are available, but functional gene annotation is less well developed than for other model organisms. More annotations could lead to a better understanding of the pathways for growth, plant colonization, and nitrogen fixation in . In this study, we present a pipeline that combines novel scores from gene coexpression network analysis in a principled way to identify the genes that are associated with certain growth conditions or highly coexpressed with a predefined set of genes of interest. This association may lead to putative functional annotation or to a prioritized list of genes for further study.

摘要

豆类的氮吸收是由细菌(如)等促进的。对于这种细菌,有基因表达数据,但功能基因注释的发展不如其他模式生物完善。更多的注释可以帮助我们更好地理解在 (细菌名称)中生长、植物定殖和固氮的途径。在这项研究中,我们提出了一个结合了基因共表达网络分析的新方法,通过这个方法来识别与某些生长条件相关或与一组预定的感兴趣基因高度共表达的基因。这种关联可能导致推测的功能注释,或者是一组优先基因的列表,以供进一步研究。

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