Alexander Partin

According to our database, Alexander Partin authored at least 10 papers between 2020 and 2023.

Collaborative distances:

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

2023

Entropy-Based Regularization on Deep Learning Models for Anti-Cancer Drug Response Prediction.

Oleksandr Narykov, Yitan Zhu, Thomas S. Brettin, Yvonne A. Evrard, Alexander Partin, Maulik Shukla, Priyanka Vasanthakumari, James H. Doroshow, Rick Stevens

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

An Automation Framework for Comparison of Cancer Response Models Across Configurations.

Justin M. Wozniak, Rajeev Jain, Andreas Wilke, Rylie Weaver, Alexander Partin, Thomas S. Brettin, Rick Stevens

Proceedings of the 19th IEEE International Conference on e-Science, 2023

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 Overbeek, Rick L. Stevens

CoRR, 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, Jason Gans, Stewart He, Pinyi Lu, Sergei Maslov, Alexander Partin, Maulik Shukla, Eric A. Stahlberg, Justin M. Wozniak, Hyun Seung Yoo, George F. Zaki, Yitan Zhu, Rick Stevens

Briefings Bioinform., 2022

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

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, Nicola Scafuri, Sauro Succi, Dieter Kranzlmüller, Gerald Mathias, David Wifling, Yann Donon, Alberto Di Meglio, Sofia Vallecorsa, Heng Ma, Anda Trifan, Arvind Ramanathan, Tom Brettin, Alexander Partin, Fangfang Xia, Xiaotan Duan, Rick Stevens, Peter V. Coveney

CoRR, 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

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, Tom Gibbs, Shantenu Jha, Kristopher Keipert, Dieter Kranzlmüller, Thorsten Kurth, Hyungro Lee, Zhuozhao Li, Heng Ma, Gerald Mathias, André Merzky, Alexander Partin, Arvind Ramanathan, Ashka Shah, Abraham C. Stern, Rick Stevens, Li Tan, Mikhail Titov, Anda Trifan, Aristeidis Tsaris, Matteo Turilli, Huub J. J. Van Dam, Shunzhou Wan, David Wifling, Junqi Yin

Proceedings of the ICPP 2021: 50th International Conference on Parallel Processing, Lemont, IL, USA, August 9, 2021

2020

Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response.

Yitan Zhu, Thomas S. Brettin, Yvonne A. Evrard, Alexander Partin, Fangfang Xia, Maulik Shukla, Hyun Seung Yoo, James H. Doroshow, Rick Stevens

CoRR, 2020

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