Using Compiler Directives for Performance Portability in Scientific Computing: Kernels from Molecular Simulation. - Ada Sedova; Andreas F. Tillack; Arnold N. Tharrington (WACCPD@SC, 2018)

Highly Interactive, Steered Scientific Workflows on HPC Systems: Optimizing Design Solutions. - John R. Ossyra; Ada Sedova; Matthew B. Baker; Jeremy C. Smith (ISC Workshops, 2019)

Porting Adaptive Ensemble Molecular Dynamics Workflows to the Summit Supercomputer. - John R. Ossyra; Ada Sedova; Arnold N. Tharrington; Frank Noé; Cecilia Clementi; Jeremy C. Smith (ISC Workshops, 2019)

GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research. - Scott LeGrand; Aaron Scheinberg; Andreas F. Tillack; Mathialakan Thavappiragasam; Josh Vincent Vermaas; Rupesh Agarwal; Jeff Larkin; Duncan Poole; Diogo Santos-Martins; Leonardo Solis-Vasquez; Andreas Koch 001; Stefano Forli; et al. (BCB, 2020)

Performance Portability of Molecular Docking Miniapp On Leadership Computing Platforms. - Mathialakan Thavappiragasam; Aaron Scheinberg; Wael R. Elwasif; Oscar R. Hernandez; Ada Sedova (P3HPC@SC, 2020)

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. - Atanu Acharya; Rupesh Agarwal; Matthew B. Baker; Jérôme Baudry; Debsindhu Bhowmik; Swen Böhm; Kendall G. Byler; Sam Yen-Chi Chen; Leighton Coates; Connor J. Cooper; Omar Demerdash; Isabella Daidone; et al. (J. Chem. Inf. Model., 2020)

Modeling protein structures from predicted contacts with modern molecular dynamics potentials: accuracy, sensitivity, and refinement. - Russell B. Davidson; Mathialakan Thavappiragasam; T. Chad Effler; Jess Woods; Dwayne A. Elias; Jerry M. Parks; Ada Sedova (BCB, 2021)

Addressing Load Imbalance in Bioinformatics and Biomedical Applications: Efficient Scheduling across Multiple GPUs. - Mathialakan Thavappiragasam; Vivek Kale; Oscar R. Hernandez; Ada Sedova (BIBM, 2021)

High-Performance Deep Learning Toolbox for Genome-Scale Prediction of Protein Structure and Function. - Mu Gao; Peik Lund-Andersen; Alex Morehead; Sajid Mahmud; Chen Chen; Xiao Chen; Nabin Giri; Raj S. Roy; Farhan Quadir; T. Chad Effler; Ryan Prout; Subil Abraham; et al. (MLHPC@SC, 2021)

DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction. - Alex Morehead; Chen Chen; Ada Sedova; Jianlin Cheng (CoRR, 2021)

Supercomputing Pipelines Search for Therapeutics Against COVID-19. - Josh Vincent Vermaas; Ada Sedova; Matthew B. Baker; Swen Boehm; David M. Rogers 001; Jeff Larkin; Jens Glaser; Micholas Dean Smith; Oscar R. Hernandez; Jeremy C. Smith (Comput. Sci. Eng., 2021)

High-throughput virtual laboratory for drug discovery using massive datasets. - Jens Glaser; Josh Vincent Vermaas; David M. Rogers 001; Jeff Larkin; Scott LeGrand; Swen Boehm; Matthew B. Baker; Aaron Scheinberg; Andreas F. Tillack; Mathialakan Thavappiragasam; Ada Sedova; Oscar R. Hernandez (Int. J. High Perform. Comput. Appl., 2021)

DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction. - Alex Morehead; Chen Chen; Ada Sedova; Jianlin Cheng (Zenodo, 2021)

Portability for GPU-accelerated molecular docking applications for cloud and HPC: can portable compiler directives provide performance across all platforms? - Mathialakan Thavappiragasam; Wael R. Elwasif; Ada Sedova (CCGRID, 2022)

Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer. - Mu Gao; Mark Coletti; Russell B. Davidson; Ryan Prout; Subil Abraham; Benjamín Hernández; Ada Sedova (IPDPS Workshops, 2022)

OpenMDlr: parallel, open-source tools for general protein structure modeling and refinement from pairwise distances. - Russell B. Davidson; Jess Woods; T. Chad Effler; Mathialakan Thavappiragasam; Julie C. Mitchell; Jerry M. Parks; Ada Sedova (Bioinform., 2022)

Multiobjective Hyperparameter Optimization for Deep Learning Interatomic Potential Training Using NSGA-II. - Mark Coletti; Ada Sedova; Rajni Chahal; Luke Gibson; Santanu Roy; Vyacheslav Bryantsev (ICPP Workshops, 2023)

DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction (Supplementary Data). - Alex Morehead; Chen Chen; Ada Sedova; Jianlin Cheng (Zenodo, 2023)

DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction (Supplementary Data). - Alex Morehead; Chen Chen; Ada Sedova; Jianlin Cheng (Zenodo, 2023)

tinyIFD: A High-Throughput Binding Pose Refinement Workflow Through Induced-Fit Ligand Docking. - Darren J. Hsu; Russell B. Davidson; Ada Sedova; Jens Glaser (J. Chem. Inf. Model., 2023)

Predicted structural proteome of Sphagnum divinum and proteome-scale annotation. - Russell B. Davidson; Mark Coletti; Mu Gao; Bryan Piatkowski; Avinash Sreedasyam; Farhan Quadir; David J. Weston; Jeremy Schmutz; Jianlin Cheng; Jeffrey Skolnick; Jerry M. Parks; Ada Sedova (Bioinform., 2023)

Impacts of floating-point non-associativity on reproducibility for HPC and deep learning applications. - Sanjif Shanmugavelu; Mathieu Taillefumier; Christopher Culver; Oscar R. Hernandez; Mark Coletti; Ada Sedova (SC Workshops, 2024)

Robustness of Deep Learning Classification to Adversarial Input on GPUs: Asynchronous Parallel Accumulation Is a Source of Vulnerability. - Sanjif Shanmugavelu; Mathieu Taillefumier; Christopher Culver; Vijay Ganesh 001; Oscar R. Hernandez; Ada Sedova (Euro-Par (2), 2025)