20 citations · 55 across the 11 of their papers we have counts for
4 papers · 1 filter
Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks
Ryien Hosseini, Filippo Simini, Austin Clyde +1
The process of screening molecules for desirable properties is a key step in several applications, ranging from drug discovery to material design. During the process of drug discov…
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…
Scaffold Embeddings: Learning the Structure Spanned by Chemical Fragments, Scaffolds and Compounds
Austin Clyde, Arvind Ramanathan, Rick Stevens
Molecules have seemed like a natural fit to deep learning's tendency to handle a complex structure through representation learning, given enough data. However, this often continuou…
A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep Learning
Austin Clyde, Tom Brettin, Alexander Partin +6
By combining various cancer cell line (CCL) drug screening panels, the size of the data has grown significantly to begin understanding how advances in deep learning can advance dru…