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Gene Families

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...

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Updated: Jun 25, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

ReactomeGSA:新的功能简化了公共数据的再利用.

Alexander Grentner¹, Eliot Ragueneau², Chuqiao Gong²

¹Department of Dermatology, Medical University of Vienna, Vienna 1090, Austria.

Bioinformatics (Oxford, England)

|May 28, 2024

概括

此摘要是机器生成的。

现在ReactomeGSA通过新的Python加载器和增强的搜索功能提供了公共多omics数据集的简化集成. 此更新改进了可访问性和跨物种的比较途径分析.

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Published on: August 25, 2021

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Last Updated: Jun 25, 2025

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Published on: August 25, 2021

科学领域:

生物信息学是一种生物信息学.
计算生物学计算生物学
基因组学就是基因组学.

背景情况:

ReactomeGSA是Reactome知识库中的一个领先的多omics路径分析平台.
它支持对各种'omics'数据类型的定量途径分析以及跨数据集和物种的比较分析.

研究的目的:

介绍ReactomeGSA的重大更新,简化公共数据的整合和重用.
增强平台使用公开可用的数据集进行比较路径分析的能力.

主要方法:

开发了"绿色加载器"Python应用程序,从GREIN资源中获取实验.
综合支持EMBL-EBI的表达图谱和GEO RNA-seq实验互动导航器.
实现了跨支持资源的公共数据集的新型搜索功能.
完全重新开发了ReactomeGSA网络前端和R/生物导体包.

主要成果:

启用了来自GREIN,Expression Atlas和GEO的公共数据集的直接获取和集成.
引入了一个统一的搜索界面,用于发现公共数据集.
通过重新开发的Web前端和R.包,简化了用户体验.
简化了跨多个数据集和物种的比较路径分析.

结论:

更新后的ReactomeGSA平台显著提高了用于路径分析的公共多omics数据的可访问性和可用性.
这些新功能简化了比较途径分析,促进了更广泛的科学发现.
该平台通过Web界面,R/生物导体包和Python应用程序即可使用.