Get Started
Home
Topics
Search
Library
Research questionHow can cell embeddings capture subcellular organization from transcriptomic and protein structural information?Holistic cell embeddings can obscure where molecules reside and how protein structure relates to their functions. This makes it difficult to preserve spatially organized biological information when combining transcriptomic and protein-level signals.
AI
Health
Machine Learning
Multimodal Models
Research Paper
Latest papersRecent research connected to this question, newest first.Subcellularly Resolved Single-Cell Embedding Learning with Transcriptomic data, Protein Structure and Localization InformationThe source describes a cross-attention framework that integrates RNA expression, protein sequence representations, and protein structural information while modeling interactions within distinct subcellular compartments. The supplied evidence establishes the embedding objective and modalities but does not specify datasets or downstream validation.research paper · Sep 2, 2026
Related questions
How can self-supervised representations transfer reliably across microscopy datasets with scarce labels and mismatched staining or channels?How can whole-slide image classifiers preserve irregular tissue regions while modeling relationships across spatially separated regions?How can protein annotation remain reliable in crowded cryo-ET volumes with limited-angle, corrupted reconstructions?How can molecular property predictors retain substructure and graph-distance information in compact representations without external pretraining?