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Found 3 papers, 1 papers with code
NodeCoder: a graph-based machine learning platform to predict active sites of modeled protein structures
While accurate protein structure predictions are now available for nearly every observed protein sequence, predicted structures lack much of the functional context offered by experimental structure determination.
Learning across label confidence distributions using Filtered Transfer Learning
In this work, we apply a transfer learning approach to improve predictive power in noisy data systems with large variable confidence datasets.
Predicting drug properties with parameter-free machine learning: Pareto-Optimal Embedded Modeling (POEM)
The prediction of absorption, distribution, metabolism, excretion, and toxicity (ADMET) of small molecules from their molecular structure is a central problem in medicinal chemistry with great practical importance in drug discovery.
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