Tag: molecular fingerprints

A new study shows that generative large language models can predict odor quality, capture concentration-dependent scent shifts, and outperform molecular ...

Researchers combined machine learning and deep learning with multiple molecular fingerprints to build predictive models that identified two promising topoisomerase ...

Researchers have built a fully open-source KNIME machine-learning workflow that curates thousands of PD-L1 bioactivity records and reliably predicts inhibitor ...

A leakage-aware, auditable computational framework trained on LINCS L1000 signatures identifies class I HDAC inhibitors, led by Mocetinostat, as top ...