A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep Learning. - Austin Clyde; Tom Brettin; Alexander Partin; Maulik Shaulik; Hyun Seung Yoo; Yvonne A. Evrard; Yitan Zhu; Fangfang Xia; Rick Stevens (CoRR, 2020)

Regression Enrichment Surfaces: a Simple Analysis Technique for Virtual Drug Screening Models. - Austin Clyde; Xiaotian Duan; Rick Stevens (CoRR, 2020)

Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release. - Yadu N. Babuji; Ben Blaiszik; Tom Brettin; Kyle Chard; Ryan Chard; Austin Clyde; Ian T. Foster; Zhi Hong; Shantenu Jha; Zhuozhao Li; Xuefeng Liu; Arvind Ramanathan; et al. (CoRR, 2020)

Scalable HPC and AI Infrastructure for COVID-19 Therapeutics. - Hyungro Lee; André Merzky; Li Tan; Mikhail Titov; Matteo Turilli; Dario Alfè; Agastya Bhati; Alex Brace; Austin Clyde; Peter V. Coveney; Heng Ma; Arvind Ramanathan; et al. (CoRR, 2020)

IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. - Aymen Al Saadi; Dario Alfè; Yadu N. Babuji; Agastya Bhati; Ben Blaiszik; Alexander Brace; Thomas S. Brettin; Kyle Chard; Ryan Chard; Austin Clyde; Peter V. Coveney; Ian T. Foster; et al. (ICPP, 2021)

Stream-AI-MD: streaming AI-driven adaptive molecular simulations for heterogeneous computing platforms. - Alexander Brace; Michael Salim; Vishal Subbiah; Heng Ma; Murali Emani; Anda Trifan; Austin R. Clyde; Corey Adams; Thomas D. Uram; Hyun Seung Yoo; Andew Hock; Jessica Liu; et al. (PASC, 2021)

Scalable HPC & AI infrastructure for COVID-19 therapeutics. - Hyungro Lee; André Merzky; Li Tan; Mikhail Titov; Matteo Turilli; Dario Alfè; Agastya Bhati; Alex Brace; Austin Clyde; Peter V. Coveney; Heng Ma; Arvind Ramanathan; et al. (PASC, 2021)

Learning curves for drug response prediction in cancer cell lines. - Alexander Partin; Thomas S. Brettin; Yvonne A. Evrard; Yitan Zhu; Hyun Seung Yoo; Fangfang Xia; Songhao Jiang; Austin Clyde; Maulik Shukla; Michael Fonstein; James H. Doroshow; Rick L. Stevens (BMC Bioinform., 2021)

Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers. - Agastya P. Bhati; Shunzhou Wan; Dario Alfè; Austin R. Clyde; Mathis Bode; Li Tan; Mikhail Titov; André Merzky; Matteo Turilli; Shantenu Jha; Roger R. Highfield; Walter Rocchia; et al. (CoRR, 2021)

Scaffold Embeddings: Learning the Structure Spanned by Chemical Fragments, Scaffolds and Compounds. - Austin Clyde; Arvind Ramanathan; Rick Stevens (CoRR, 2021)

Protein-Ligand Docking Surrogate Models: A SARS-CoV-2 Benchmark for Deep Learning Accelerated Virtual Screening. - Austin Clyde; Thomas S. Brettin; Alexander Partin; Hyun Seung Yoo; Yadu N. Babuji; Ben Blaiszik; André Merzky; Matteo Turilli; Shantenu Jha; Arvind Ramanathan; Rick Stevens (CoRR, 2021)

AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics. - Lorenzo Casalino; Abigail C. Dommer; Zied Gaieb; Emília P. Barros; Terra Sztain; Surl-Hee Ahn; Anda Trifan; Alexander Brace; Anthony T. Bogetti; Austin Clyde; Heng Ma; Hyungro Lee; et al. (Int. J. High Perform. Comput. Appl., 2021)

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery. - Yulun Wu; Nicholas Choma; Andrew Deru Chen; Mikaela Cashman; Érica Teixeira Prates; Verónica G. Melesse Vergara; Manesh Shah; Austin Clyde; Thomas S. Brettin; Wibe Albert de Jong; Neeraj Kumar; Martha S. Head; et al. (ICLR, 2022)

A cross-study analysis of drug response prediction in cancer cell lines. - Fangfang Xia; Jonathan E. Allen; Prasanna Balaprakash; Thomas S. Brettin; Cristina Garcia-Cardona; Austin Clyde; Judith D. Cohn; James H. Doroshow; Xiaotian Duan; Veronika Dubinkina; Yvonne A. Evrard; Ya Ju Fan; et al. (Briefings Bioinform., 2022)

Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks. - Ryien Hosseini; Filippo Simini; Austin Clyde; Arvind Ramanathan (CoRR, 2022)

Deep learning methods for drug response prediction in cancer: predominant and emerging trends. - Alexander Partin; Thomas S. Brettin; Yitan Zhu; Oleksandr Narykov; Austin Clyde; Jamie C. Overbeek; Rick L. Stevens (CoRR, 2022)

Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action. - Anda Trifan; Defne Gorgun; Michael Salim; Zongyi Li; Alexander Brace; Maxim Zvyagin; Heng Ma; Austin Clyde; David Clark; David J. Hardy; Tom Burnley; Lei Huang 019; et al. (Int. J. High Perform. Comput. Appl., 2022)

High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor. - Austin Clyde; Stephanie Galanie; Daniel W. Kneller; Heng Ma; Yadu N. Babuji; Ben Blaiszik; Alexander Brace; Thomas S. Brettin; Kyle Chard; Ryan Chard; Leighton Coates; Ian T. Foster; et al. (J. Chem. Inf. Model., 2022)

AI for science and global citizens. - Austin Clyde (Patterns, 2022)

Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats. - Wei Chen 043; Yihui Ren 001; Ai Kagawa; Matthew R. Carbone; Samuel Yen-Chi Chen; Xiaohui Qu; Shinjae Yoo; Austin Clyde; Arvind Ramanathan; Rick L. Stevens; Hubertus Van Dam; Deyu Lu (ICMLA, 2023)

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. - Shuaiwen Leon Song; Bonnie Kruft; Minjia Zhang; Conglong Li; Shiyang Chen 004; Chengming Zhang 006; Masahiro Tanaka; Xiaoxia Wu; Jeff Rasley; Ammar Ahmad Awan; Connor Holmes; Martin Cai; et al. (CoRR, 2023)

#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol. - Abigail C. Dommer; Lorenzo Casalino; Fiona L. Kearns; Mia A. Rosenfeld; Nicholas Wauer; Surl-Hee Ahn; John Russo 003; A. Sofia F. Oliveira; Clare Morris; Anthony T. Bogetti; Anda Trifan; Alexander Brace; et al. (Int. J. High Perform. Comput. Appl., 2023)

AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2. - Rajendra P. Joshi; Katherine J. Schultz; Jesse William Wilson; Agustin Kruel; Rohith Anand Varikoti; Chathuri J. Kombala; Daniel W. Kneller; Stephanie Galanie; Gwyndalyn Phillips; Qiu Zhang; Leighton Coates; Jyothi Parvathareddy; et al. (J. Chem. Inf. Model., 2023)

ChemoGraph: Interactive Visual Exploration of the Chemical Space. - Bharat Kale; Austin Clyde; Maoyuan Sun; Arvind Ramanathan; Rick Stevens; Michael E. Papka (Comput. Graph. Forum, 2023)

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. - Maxim Zvyagin; Alexander Brace; Kyle Hippe; Yuntian Deng; Bin Zhang; Cindy Orozco Bohorquez; Austin Clyde; Bharat Kale; Danilo Perez-Rivera; Heng Ma; Carla M. Mann; Michael W. Irvin; et al. (Int. J. High Perform. Comput. Appl., 2023)

Assessing Reusability of Deep Learning-Based Monotherapy Drug Response Prediction Models Trained with Omics Data. - Jamie C. Overbeek; Alexander Partin; Thomas S. Brettin; Nicholas Chia; Oleksandr Narykov; Priyanka Vasanthakumari; Andreas Wilke; Yitan Zhu; Austin Clyde; Sara Jones; Rohan Gnanaolivu; Yuanhang Liu; et al. (CoRR, 2024)