CODEX, a neural network approach to explore signaling dynamics landscapes

Fluorescent biosensors routinely yield thousands of single-cell, heterogeneous, multi-dimensional 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.

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