35 citations · 101 across the 12 of their papers we have counts for
5 papers · 1 filter
CrossedWires: A Dataset of Syntactically Equivalent but Semantically Disparate Deep Learning Models
Max Zvyagin, Thomas Brettin, Arvind Ramanathan +1
The training of neural networks using different deep learning frameworks may lead to drastically differing accuracy levels despite the use of the same neural network architecture a…
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…
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery
Yulun Wu, Mikaela Cashman, Nicholas Choma +13
We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined…
A cross-study analysis of drug response prediction in cancer cell lines
Fangfang Xia, Jonathan Allen, Prasanna Balaprakash +21
To enable personalized cancer treatment, machine learning models have been developed to predict drug response as a function of tumor and drug features. However, most algorithm deve…
Pandemic Drugs at Pandemic Speed: Infrastructure for Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers
Agastya P. Bhati, Shunzhou Wan, Dario Alfè +26
The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottle…