Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps

Keyphrases

• Multiplexing 100%
• Protein Map 100%
• Molecular Composition 66%
• RNA Synthesis 66%
• Pixel Analysis 66%
• Conditional Autoencoder 66%
• High-resolution 33%
• Pixel Level 33%
• Cell Size 33%
• Deep Learning Framework 33%
• Spatial Context 33%
• Multiple Length Scales 33%
• Spatial Organization 33%
• Cellular Heterogeneity 33%
• Organization Change 33%
• Multiplexed Imaging 33%
• Experimental Perturbation 33%
• RNA Processing 33%
• Cellular Phenotype 33%
• Synthesis Rate 33%
• Heterogeneous Cell Population 33%
• Systematic Mapping Study 33%
• Biological Organization 33%
• Multiplexed Immunofluorescence 33%
• Subcellular Organization 33%
• Membraneless Organelles 33%
• Conditional Variational Autoencoder 33%

Biochemistry, Genetics and Molecular Biology

• RNA Synthesis 100%
• Immunofluorescence 50%
• Volume 50%
• RNA Processing 50%
• Cell Size 50%