AI Research
DELBERT-2: Pretrained Fingerprint Language Models for DEL Protein Binder Prediction
A ModernBERT encoder learns molecular fingerprint sequences from 2.5 million DEL compounds
We present DELBERT-2, a pretrained fingerprint language model that converts sparse molecular fingerprints into unified token sequences using a ModernBERT encoder trained with masked language modelling on 2.5M molecules from the AIRCHECK DEL corpus.
AC
ArXiv CS.LG
Source
ArXiv CS.LG
AI Analysis
Generated insight by OnAirToday AI
This approach applies language-model pretraining to sparse molecular fingerprints, offering a way to learn shared representations from a large compound collection. Its relevance to DEL protein binder prediction depends on how well those representations support that task.
Powered by AI • Not a substitute for human analysisMore Insights →
Share
Filed under:AI Research
Comments
Keep comments relevant and respectful. No links, advertising, self-promotion, or spam.