Ada Sedova

According to our database, Ada Sedova authored at least 18 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Predicted structural proteome of <i>Sphagnum divinum</i> 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., August, 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., June, 2023

Multiobjective Hyperparameter Optimization for Deep Learning Interatomic Potential Training Using NSGA-II.

Mark Coletti, Ada Sedova, Rajni Chahal, Luke Gibson, Santanu Roy, Vyacheslav Bryantsev

Proceedings of the 52nd International Conference on Parallel Processing Workshops, 2023

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

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

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

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

Proceedings of the 22nd IEEE International Symposium on Cluster, 2022

2021

High-throughput virtual laboratory for drug discovery using massive datasets.

Jens Glaser, Josh Vincent Vermaas, David M. Rogers, 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

Supercomputing Pipelines Search for Therapeutics Against COVID-19.

Josh Vincent Vermaas, Ada Sedova, Matthew B. Baker, Swen Boehm, David M. Rogers, Jeff Larkin, Jens Glaser, Micholas Dean Smith, Oscar R. Hernandez, Jeremy C. Smith

Comput. Sci. Eng., 2021

DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction.

Alex Morehead, Chen Chen, Ada Sedova, Jianlin Cheng

CoRR, 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, Wael R. Elwasif, Nicholas Quentin Haas, Jeffrey Skolnick, Jianlin Cheng, Ada Sedova

Proceedings of the IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2021

Addressing Load Imbalance in Bioinformatics and Biomedical Applications: Efficient Scheduling across Multiple GPUs.

Mathialakan Thavappiragasam, Vivek Kale, Oscar R. Hernandez, Ada Sedova

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

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

Proceedings of the BCB '21: 12th ACM International Conference on Bioinformatics, 2021

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, John D. Eblen, Sally R. Ellingson, Stefano Forli, Jens Glaser, James C. Gumbart, John Gunnels, Oscar R. Hernandez, Stephan Irle, Daniel W. Kneller, Andrey Kovalevsky, Jeffrey M. Larkin, Travis J. Lawrence, Scott LeGrand, Shih-Hsien Liu, Julie C. Mitchell, Gilchan Park, Jerry M. Parks, Anna Pavlova, Loukas Petridis, Duncan Poole, Line Pouchard, Arvind Ramanathan, David M. Rogers, Diogo Santos-Martins, Aaron Scheinberg, Ada Sedova, Yue Shen, Jeremy C. Smith, Micholas Dean Smith, Carlos Soto, Aristides Tsaris, Mathialakan Thavappiragasam, Andreas F. Tillack, Josh Vincent Vermaas, Van Quan Vuong, Junqi Yin, Shinjae Yoo, Mai Zahran, Laura Zanetti Polzi

J. Chem. Inf. Model., 2020

Performance Portability of Molecular Docking Miniapp On Leadership Computing Platforms.

Mathialakan Thavappiragasam, Aaron Scheinberg, Wael R. Elwasif, Oscar R. Hernandez, Ada Sedova

Proceedings of the IEEE/ACM International Workshop on Performance, 2020

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, Stefano Forli, Oscar R. Hernandez, Jeremy C. Smith, Ada Sedova

Proceedings of the BCB '20: 11th ACM International Conference on Bioinformatics, 2020

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

Proceedings of the High Performance Computing, 2019

Highly Interactive, Steered Scientific Workflows on HPC Systems: Optimizing Design Solutions.

John R. Ossyra, Ada Sedova, Matthew B. Baker, Jeremy C. Smith

Proceedings of the High Performance Computing, 2019

2018

Using Compiler Directives for Performance Portability in Scientific Computing: Kernels from Molecular Simulation.

Ada Sedova, Andreas F. Tillack, Arnold N. Tharrington

Proceedings of the Accelerator Programming Using Directives - 5th International Workshop, 2018