2 papers
cs.LG2025
Uncertainty-Guided Model Selection for Tabular Foundation Models in Biomolecule Efficacy Prediction
Jie Li, Andrew McCarthy, Zhizhuo Zhang +1
In-context learners like TabPFN are promising for biomolecule efficacy prediction, where established molecular feature sets and relevant experimental results can serve as powerful…
q-bio.GN2024
Fine-tuning Protein Language Models with Deep Mutational Scanning improves Variant Effect Prediction
Aleix Lafita, Ferran Gonzalez, Mahmoud Hossam +5
Protein Language Models (PLMs) have emerged as performant and scalable tools for predicting the functional impact and clinical significance of protein-coding variants, but they sti…