20 citations · 84 across the 16 of their papers we have counts for
4 papers · 1 filter
Assessing Reusability of Deep Learning-Based Monotherapy Drug Response Prediction Models Trained with Omics Data
Jamie C. Overbeek, Alexander Partin, Thomas S. Brettin +21
Cancer drug response prediction (DRP) models present a promising approach towards precision oncology, tailoring treatments to individual patient profiles. While deep learning (DL)…
Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats
Wei Chen, Yihui Ren, Ai Kagawa +9
Fast screening of drug molecules based on the ligand binding affinity is an important step in the drug discovery pipeline. Graph neural fingerprint is a promising method for develo…
Protein-Ligand Docking Surrogate Models: A SARS-CoV-2 Benchmark for Deep Learning Accelerated Virtual Screening
Austin Clyde, Thomas Brettin, Alexander Partin +8
We propose a benchmark to study surrogate model accuracy for protein-ligand docking. We share a dataset consisting of 200 million 3D complex structures and 2D structure scores acro…
Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release
Yadu Babuji, Ben Blaiszik, Tom Brettin +15
Researchers across the globe are seeking to rapidly repurpose existing drugs or discover new drugs to counter the the novel coronavirus disease (COVID-19) caused by severe acute re…