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Biological Image Indexing for Content-Based Retrieval of Drug Effects in Phenotypic Screening Data of Macroparasites

机译:寄生虫表型筛选数据中基于效果的基于药物作用的生物图像检索检索

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Phenotypic-screening involves systematically assessing the therapeutic effects of a set of molecules by exposing entire disease systems to them and observing, through imaging, the effects of the compounds. Phenotypic assays typically generate hundreds of thousands to millions of images. An unmet challenge in this setting is to identify similar phenotypic effects caused by molecules, which may potentially be structurally different. While phenotypes can be compared using their feature vectors, real-time querying of these data sets becomes a challenging task because of the size of the data sets and the high dimensionality of the feature vectors. In this paper, we present an indexing approach that seeks to address this problem and allows efficient query-retrieval of phenotypic drug effects.
机译:表型筛选包括通过将整个疾病系统暴露于分子中并通过成像观察化合物的作用来系统地评估一组分子的治疗效果。表型化验通常会产生数十万到数百万个图像。在这种情况下,一个尚未满足的挑战是确定由分子引起的相似表型效应,这可能在结构上有所不同。尽管可以使用它们的特征向量来比较表型,但是由于数据集的大小和特征向量的高维性,实时查询这些数据集成为一项艰巨的任务。在本文中,我们提出了一种索引方法,旨在解决此问题并允许对表型药物作用进行有效的查询检索。

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