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SCENERY: AWeb-Based Application for Network Reconstruction and Visualization of Cytometry Data

机译:风景:基于AWEB的网络重建应用和细胞测量数据的可视化

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Cytometry techniques allowto quantifymorphological characteristics and protein abundances at a single-cell level. Data collected with these techniques can be used for addressing the fascinating, yet challenging problem of reconstructing the network of protein interactions forming signaling pathways and governing cell biological mechanisms. Network reconstruction is an established and well studied problem in the machine learning and data mining fields, with several algorithms already available. In this paper,we present the firstweb-oriented application, SCENERY, that allows scientists to rapidly apply state-of-the-art network-reconstruction methods on cytometry data. SCENERY comes with an easy-to-use user interface, a modular architecture, and advanced visualization functions. The functionalities of the application are illustrated on data from a publicly available immunology experiment.
机译:细胞测定技术允许量化常规特征和蛋白质丰度在单细胞水平。采用这些技术收集的数据可用于解决重建形成信号传导途径和控制细胞生物机制的诱人的,但重构蛋白质相互作用网络的迷人问题。网络重建是机器学习和数据挖掘领域的建立和良好的问题,具有几种算法已经可用。在本文中,我们介绍了先进的前途的应用,风景,允许科学家们在细胞谱系数据迅速应用最先进的网络重建方法。风景附带易于使用的用户界面,模块化架构和高级可视化功能。申请的功能是关于来自公开免疫学实验的数据。

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