Zoomable Cell

第二阶段的主要目标是将第一阶段开发的技术适应和推广到地形数据。这些数据来自机器人显微镜技术，该技术可以以200纳米的分辨率获取完整人类细胞内许多不同蛋白质的体积密度。其中一些蛋白质作为细胞隔间和结构的标志物，另一些则提供代谢过程的洞察力。多通道体积蛋白质数据允许以几何方式重建获得的细胞的细胞隔间。当在3D浏览器中放大到这些结构时，复合体和蛋白质的结构3D模型将根据测量的蛋白质密度分布。重建的人体细胞将通过刷子和链接技术链接到蛋白质网络的交互式图形可视化，例如，协同定位或相互作用网络。这将首次在完整细胞定位数据的帮助下分析蛋白质网络。应用包括相互作用网络的验证、功能通路的分析和蛋白质通过细胞的运输分析。我们计划在上皮细胞上示范探索这种方法。

The key goal of phase 2 is to adapt and extend the techniques developed in phase 1 to toponomics data. This data comes from a robotic microscopy technique, which allows acquisition of the volumetric density for many different proteins inside intact human cells with a resolution of 200nm. Some of these proteins act as landmarks of cellular compartments and structure, others give insights to metabolic processes.The multi-channel volumetric protein data allows to reconstruct cellular compartments of the acquired cells geometrically. When zooming onto these structures in the 3D browser, structural 3D models of complexes and proteins will be distributed according to the measured protein densities.The reconstructed human cell will be linked through brush and link techniques to an interactive graph visualization of protein networks that can be for example co-location or interaction networks. This will allow for the first time to analyze protein networks with the help of localization data from an intact cell.Applications include validation of interaction networks, analysis of functional pathways and analysis of protein transport through the cell. We plan to explore this approach exemplarily on epithelial cells.