Screenit: Visual Analysis of Cellular Screens
Screenit: Visual Analysis of Cellular Screens
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Screenit：细胞屏幕的视觉分析
DOI：
10.1109/tvcg.2016.2598587
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发表时间：
2017
影响因子：
5.2
通讯作者：
H. Pfister
中科院分区：
文献类型：
--
作者：
K. Dinkla;Hendrik Strobelt;Bryan Genest;S. Reiling;M. Borowsky;H. Pfister
高通量和高含量筛选使细胞培养物暴露于多种药物的大规模、成本效益高的实验成为可能。由此产生的多变量数据集具有大而浅的层次结构。这种结构的最深层用从图像数据派生的数字特征来描述单元。随后的水平描述了根据强加的实验条件(药物暴露)对细胞培养进行包络。我们介绍了ScreenIt，这是一种与筛选专家密切合作设计的可视化分析方法。ScreenIt允许在多个层次级别和多个详细级别上导航和分析多变量数据。ScreenIt集成了细胞物理状态(表型)的交互建模和药物对细胞培养的影响(HITS)。此外，通过检测表明低质量数据的异常情况来实现质量控制，同时提供旨在与筛选专家的工作流程相匹配的界面。我们演示了对现实世界数据集CellMorph的分析，该数据集包含20,000个细胞培养的600万个细胞。
High-throughput and high-content screening enables large scale, cost-effective experiments in which cell cultures are exposed to a wide spectrum of drugs. The resulting multivariate data sets have a large but shallow hierarchical structure. The deepest level of this structure describes cells in terms of numeric features that are derived from image data. The subsequent level describes enveloping cell cultures in terms of imposed experiment conditions (exposure to drugs). We present Screenit, a visual analysis approach designed in close collaboration with screening experts. Screenit enables the navigation and analysis of multivariate data at multiple hierarchy levels and at multiple levels of detail. Screenit integrates the interactive modeling of cell physical states (phenotypes) and the effects of drugs on cell cultures (hits). In addition, quality control is enabled via the detection of anomalies that indicate low-quality data, while providing an interface that is designed to match workflows of screening experts. We demonstrate analyses for a real-world data set, CellMorph, with 6 million cells across 20,000 cell cultures.
影响因子：
2.3
作者：
Graham, Martin;Kennedy, Jessie
通讯作者：
Kennedy, Jessie