Austin Clyde
Publications by Year
Research Areas
Computational Drug Discovery Methods, Machine Learning in Materials Science, Protein Structure and Dynamics, Cell Image Analysis Techniques, Bioinformatics and Genomic Networks
Most-Cited Works
- → SARS-CoV-2 infects the human kidney and drives fibrosis in kidney organoids(2021)260 cited
- → AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics(2021)177 cited
- → Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors(2023)163 cited
- → Deep learning methods for drug response prediction in cancer: Predominant and emerging trends(2023)122 cited
- → High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor(2021)107 cited
- → A cross-study analysis of drug response prediction in cancer cell lines(2021)91 cited
- → #COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol(2022)90 cited
- → GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics(2023)74 cited
- → Structural, Electronic, and Electrostatic Determinants for Inhibitor Binding to Subsites S1 and S2 in SARS-CoV-2 Main Protease(2021)57 cited
- → Pandemic Drugs at Pandemic Speed: Infrastructure for Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers(2021)42 cited