We provide a:
- PyTorch code for training & inference: github.com/mehta-lab/Vi...
- A GUI to visualize trajectories in real and embedding space
- Tools for efficient human-in-the-loop annotation

DynaCLR’s temporally consistent embeddings enable in silico synchronization of asynchronous dynamics like infection & mitosis, along with organelle responses, enabling pseudotime estimation across multiple imaging channels. 5/⏳

DynaCLR embeddings enable efficient classification of cell states, including mitosis and viral infection, with a few thousand point annotations of cell state, which speeds up measurement of complex cell state dynamics. 3/🦠