6 citations · 15 across the 4 of their papers we have counts for
4 papers
Optimal Decision Making in High-Throughput Virtual Screening Pipelines
Hyun-Myung Woo, Xiaoning Qian, Li Tan +4
The need for efficient computational screening of molecular candidates that possess desired properties frequently arises in various scientific and engineering problems, including d…
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…
Scalable HPC and AI Infrastructure for COVID-19 Therapeutics
Hyungro Lee, Andre Merzky, Li Tan +15
COVID-19 has claimed more 1 million lives and resulted in over 40 million infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. In response, the DOE re…
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads
Aymen Al Saadi, Dario Alfe, Yadu Babuji +33
The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2-3 billion to deliver one new drug. This is both too expensive…