PPI2Text generates natural-language captions for protein-protein interactions from sequences by encoding each protein with ESM3, building a residue-pair map, and decoding with Qwen3 using coordinate-aligned positional encoding.
Nucleic acids research , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
AROMA combines text, graph topology, and protein sequences with augmented reasoning and two-stage optimization to deliver more accurate and interpretable predictions of genetic perturbation effects in virtual cells, outperforming baselines even in zero-shot and long-tail settings.
citing papers explorer
-
PPI2Text: Captioning Protein-Protein Interactions with Coordinate-Aligned Pair-Map Decoding
PPI2Text generates natural-language captions for protein-protein interactions from sequences by encoding each protein with ESM3, building a residue-pair map, and decoding with Qwen3 using coordinate-aligned positional encoding.
-
AROMA: Augmented Reasoning Over a Multimodal Architecture for Virtual Cell Genetic Perturbation Modeling
AROMA combines text, graph topology, and protein sequences with augmented reasoning and two-stage optimization to deliver more accurate and interpretable predictions of genetic perturbation effects in virtual cells, outperforming baselines even in zero-shot and long-tail settings.