Fluorescent biosensors routinely yield thousands of single-cell, heterogeneous, multidimensional signaling trajectories that are difficult to mine for relevant information. We present CODEX, an approach based on artificial neural networks to guide exploration of time-series datasets and to identify motifs in dynamic signaling states.

中文翻译：

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CODEX，一种探索信号动力学环境的神经网络方法

荧光生物传感器通常会产生数以千计的单细胞，异质，多维信号轨迹，这些轨迹很难挖掘相关信息。我们提出了CODEX，这是一种基于人工神经网络的方法，可指导探索时序数据集并识别动态信号状态中的图案。