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Development of an Integrated Visualization System for Phenotypic Character Networks

机译:表型字符网络集成可视化系统的开发

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Wet and dry biological data are potentially complementary. By visually integrating the initiation and developmental processes of organisms, we might reveal new causalities in biological data. Here we present an integrated visualization system for a causality network constructed from phenotypic developmental characters and their related scientific literature. To obtain the phenotypic characters, we applied bio-imaging informatics techniques to the data of wet experiments. The phenotypic character network was visually rendered in the CausalNet system, which provides both explanatory and verification visualization functions. Statistical analysis and scientific literature mining proved useful for determining the mechanisms underlying the phenotypic trait network. The validity of the system was confirmed in an application example and expert feedback on the developmental process of the nematode Caenorhabditis elegans. The discussed methodology is applicable to other multicellular organisms.
机译:干燥和干燥的生物学数据可能是互补的。通过视觉上整合生物的起始和发育过程,我们可能会揭示生物学数据中的新因果关系。在这里,我们提出了一个基于表型发展特征及其相关科学文献构建的因果关系网络的集成可视化系统。为了获得表型特征,我们将生物成像信息学技术应用于湿法实验的数据。表型字符网络在CausalNet系统中进行了可视化渲染,该系统提供了解释性和验证性可视化功能。事实证明,统计分析和科学文献挖掘对于确定表型特征网络的潜在机制很有用。该系统的有效性在一个应用实例中得到了证实,并在线虫秀丽隐杆线虫的发育过程中得到了专家的反馈。讨论的方法适用于其他多细胞生物。

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