Reconstructing signaling histories of single cells via perturbation screens and transfer learning
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TL;DR - IRIS uses transfer learning and in vitro perturbation-screen data to reconstruct signaling states and histories of individual cells across diverse in vivo contexts. This could help researchers infer past cellular signaling activity that is not directly observable from a single snapshot.
- Learns conserved representations of cell-signaling processes from perturbation data.
- Transfers those representations from controlled in vitro experiments to varied in vivo cellular contexts.
- Focuses on reconstructing both current signaling states and prior signaling histories.
- The provided abstract does not include quantitative results or benchmark details.
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Reconstructing signaling histories of single cells via perturbation screens and transfer learning
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TL;DR - IRIS uses transfer learning and in vitro perturbation-screen data to reconstruct signaling states and histories of individual cells across diverse in vivo contexts. This could help researchers infer past cellular signaling activity that is not directly observable from a single snapshot.
- Learns conserved representations of cell-signaling processes from perturbation data.
- Transfers those representations from controlled in vitro experiments to varied in vivo cellular contexts.
- Focuses on reconstructing both current signaling states and prior signaling histories.
- The provided abstract does not include quantitative results or benchmark details.