Brandon Anderson, PhD
Atomwise
Protein-Ligand Binding Predictions with SO(3)-Equivariant Neural Networks
DIVISIONCOMP
Date, time
Tuesday, April 13, 2021
2:40 pm to 3:00 pm
Jon Sorenson, PhD
Atomwise
Chimeric Molecules as Adversarial Training Examples for Machine Learning
DIVISIONCINF
Date, time
Thursday, April 15, 2021
6:30 pm to 6:50 pm
Michael Mysinger, PhD
Atomwise
Comparing Voxel-Based and Graph-Based Convolutional Neural Network Models to Quantitatively Predict Binding Affinity Globally Across Structures and Ligands
DIVISIONCOMP
Date, time
Tuesday, April 13, 2021
2:20 pm to 2:40 pm
Pawel Gniewek, PhD
Atomwise
Structure-Based Drug Design with Multi-Task Learning and Data Augmentation
DIVISIONCOMP
Date, time
Monday, April 12, 2021
10:40 am to 11:00 am
Ha Truong, PhD
Atomwise
Acceleration of TB Drug Discovery by AI-Based Virtual Screening Against Underexploited Targets
DIVISIONMEDI
COLLABORATOR, co-presenter
Kyle Rohde, PhD
Matthew Alteen, PhD
Simon Fraser University
Discovery of Novel Inhibitors of O-GlcNAc Transferase Through Structure-Based Virtual Screening
DIVISIONMEDI
ATOMWISE COLLABORATOR
Josh Goldenberg, PhD
Mostafa Ahmed, PhD
Atomwise
Artificial Intelligence Aided Discovery of New Classes of Antiprotozoal Agents for Chagas Disease
DIVISIONMEDI
COLLABORATORs
Benjamin Perry, PhD
Kong Nguyen, PhD
Navid Sobhani, PhD
Baylor College of Medicine
TITLE
Novel, Smaller and More Powerful CTLA4 Inhibitors For The Treatment of Solid Tumors
DIVISION
BIOL
ATOMWISE COLLABORATOR
Aram Davtyan, PhD
Tigran Abramyan, PhD
Atomwise
Discovery of Inhibitors of WDR Domain-Containing Proteins using a Deep Convolutional Neural Network
DIVISIONMEDI
COLLABORATORs
Structural Genomics Consortium
Join our team
Our team is comprised of over 30 PhD scientists who contribute to a high-performance academic-like culture that fosters robust scientific and technical excellence. We strongly believe that data wins over opinions, and aim for as little dogma as possible in our decision making. Learn more about our team and opportunities at Atomwise.
About our technology
AtomNet® technology was the first application of artificial intelligence/machine learning to molecular recognition. Our award-winning AtomNet® technology has been used to find small molecule hits for more undruggable targets than any other AI drug discovery platform.
