DancePartner: Python套件可以从文献和数据库中挖掘多态关系网络
David J Degnan, Clayton W Strauch, Moses Y Obiri
1Grand Valley State University, 1 Campus Drive, Allendale, Michigan 49401, United States.
Journal of proteome research
|November 4, 2025
概括
DancePartner Python 软件包通过从科学文献和数据库中提取生物分子关系来促进多态网络构建,帮助研究未经研究的物种.
科学领域:
- 系统生物学 系统生物学
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 多组学实验旨在阐明条件之间的分子生物学变化.
- 了解生物分子的关系 (例如相互作用,代谢途径) 是至关重要的.
- 现有的数据库缺乏全面的关系数据,特别是对研究不足的物种,需要文献挖掘.
研究的目的:
- 开发一种可访问的工具,从文献和数据库中提取生物分子关系.
- 创建一个Python包,DancePartner,用于自动关系提取和多omics网络构建.
- 为了使生物分子同义词的映射到标准化标识符和网络的可视化.
主要方法:
- 开发了DancePartner Python包,用于文学和数据库挖掘.
- 实现了用于生物分子同义词映射和网络可视化的功能.
- 利用了大量关于 *Caenorhabditis elegans* 和 *Saccharomyces cerevisiae* 的论文和摘要数据集.
主要成果:
- 成功地从文献和公共数据库 (KEGG,WikiPathways,UniProt,LipidMaps) 中提取和整合了生物分子关系.
- 证明了DancePartner使用*C. elegans*和*S. cerevisiae*广泛数据集的能力.
- 视觉化和描述了由此产生的多态网络,并比较了网络构建时间.
结论:
- DancePartner提供了一个可访问的解决方案,用于构建多组网络,特别是对于现有数据有限的物种.
- 该软件包有助于整合多种数据源,以进行全面的生物网络分析.
- 自动化文献挖掘和网络可视化是推动多态学研究的关键.
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