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PyPathway: Python Package for Biological Network Analysis and Visualization

机译:PyPathway:用于生物网络分析和可视化的Python软件包

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Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.
机译:生命科学研究代表着大数据集的最大产生者之一,这主要是由于快速测序技术的进步。生物网络(包括交互式网络和人类策划的路径)对于理解这些高通量数据集至关重要。生物网络分析提供了一种方法,不仅可以系统地探索特定疾病的分子复杂性,而且可以系统地探索明显不同表型之间的分子关系。当前,已经开发了一些针对Python社区的软件包,例如BioPython和Goatools。但是,仍然需要执行综合网络分析和可视化的工具。在这里,我们开发了PyPathway,这是一个可扩展的免费开源Python软件包,用于功能丰富性分析,网络建模和网络可视化。网络处理模块支持各种交互网络和路径数据库,例如Reactome,WikiPathway,STRING和BioGRID。网络分析模块实现了超额表示分析,基因集富集分析,基于网络的富集和从头网络建模。最后,可视化和数据发布模块使用户可以使用简单的Web应用程序共享其分析。有关软件包的可用性,请参阅第一个参考。

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