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预测的秀丽隐杆线虫功能相互作用组和用于差异表达基因功能解释的网络工具。

Predicted functional interactome of Caenorhabditis elegans and a web tool for the functional interpretation of differentially expressed genes.

机构信息

Institute of Pharmaceutical Biotechnology of Zhejiang University School of Medicine and Department of Radiology of the First Affiliated Hospital, Hangzhou, 310058, China.

Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, Taizhou, 318000, China.

出版信息

Biol Direct. 2020 Oct 19;15(1):20. doi: 10.1186/s13062-020-00271-6.

Abstract

BACKGROUND

The nematode worm, Caenorhabditis elegans, is a saprophytic species that has been emerging as a standard model organism since the early 1960s. This species is useful in numerous fields, including developmental biology, neurobiology, and ageing. A high-quality comprehensive molecular interaction network is needed to facilitate molecular mechanism studies in C. elegans.

RESULTS

We present the predicted functional interactome of Caenorhabditis elegans (FIC), which integrates functional association data from 10 public databases to infer functional gene interactions on diverse functional perspectives. In this work, FIC includes 108,550 putative functional associations with balanced sensitivity and specificity, which are expected to cover 21.42% of all C. elegans protein interactions, and 29.25% of these associations may represent protein interactions. Based on FIC, we developed a gene set linkage analysis (GSLA) web tool to interpret potential functional impacts from a set of differentially expressed genes observed in transcriptome analyses.

CONCLUSION

We present the predicted C. elegans interactome database FIC, which is a high-quality database of predicted functional interactions among genes. The functional interactions in FIC serve as a good reference interactome for GSLA to annotate differentially expressed genes for their potential functional impacts. In a case study, the FIC/GSLA system shows more comprehensive and concise annotations compared to other widely used gene set annotation tools, including PANTHER and DAVID. FIC and its associated GSLA are available at the website http://worm.biomedtzc.cn .

摘要

背景

线虫,秀丽隐杆线虫,是一种腐生物种,自 20 世纪 60 年代初以来,它已成为一种标准的模式生物。该物种在许多领域都有应用,包括发育生物学、神经生物学和衰老学。为了促进秀丽隐杆线虫的分子机制研究,需要一个高质量的综合分子相互作用网络。

结果

我们提出了秀丽隐杆线虫的预测功能相互作用网络(FIC),它整合了来自 10 个公共数据库的功能关联数据,从不同的功能角度推断功能基因相互作用。在这项工作中,FIC 包括 108550 个假定的功能关联,具有平衡的敏感性和特异性,预计将涵盖秀丽隐杆线虫所有蛋白质相互作用的 21.42%,其中 29.25%的这些关联可能代表蛋白质相互作用。基于 FIC,我们开发了一个基因集连锁分析(GSLA)网络工具,以从转录组分析中观察到的一组差异表达基因中解释潜在的功能影响。

结论

我们提出了预测的秀丽隐杆线虫相互作用网络数据库 FIC,这是一个高质量的基因间预测功能相互作用数据库。FIC 中的功能相互作用可以作为 GSLA 的良好参考相互作用网络,为差异表达基因的潜在功能影响进行注释。在一个案例研究中,与其他广泛使用的基因集注释工具(包括 PANTHER 和 DAVID)相比,FIC/GSLA 系统提供了更全面和简洁的注释。FIC 及其相关的 GSLA 可在网站 http://worm.biomedtzc.cn 上获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc19/7574172/1ccbad1d7ea3/13062_2020_271_Fig1_HTML.jpg

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