Papers by Nabil Ibtehaz
Protein-STORY: Semantic Text-Oriented Representation Yields biologically meaningful Protein embeddings (2026.acl-short)
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| Challenge: | Unsupervised representation learning relying on sequence data often overlooks decades of expert-curated biological knowledge stored in textual formats. |
| Approach: | They propose a pipeline that synthesizes protein embeddings from diverse, multi-source text descriptions and a network architecture that integrates high-fidelity functional and structural insights into a unified representation. |
| Outcome: | The proposed pipeline outperforms existing models on diverse downstream tasks (+2 pts F1) and enables zero-shot text-prompted protein search. |