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2020 – today
- 2024
[i9]Tianshu Feng, Rohan Gnanaolivu, Abolfazl Safikhani, Yuanhang Liu, Jun Jiang, Nicholas Chia, Alexander Partin, Priyanka Vasanthakumari, Yitan Zhu, Chen Wang:
Variational and Explanatory Neural Networks for Encoding Cancer Profiles and Predicting Drug Responses. CoRR abs/2407.04486 (2024)- [i8]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, Jun Jiang, Chen Wang, Carter Knutson, Andrew D. McNaughton, Neeraj Kumar, Gayara Demini Fernando, Souparno Ghosh, Cesar Sanchez-Villalobos, Ruibo Zhang, Ranadip Pal, M. Ryan Weil, Rick L. Stevens:
Assessing Reusability of Deep Learning-Based Monotherapy Drug Response Prediction Models Trained with Omics Data. CoRR abs/2409.12215 (2024) - 2023
- [c3]Justin M. Wozniak, Rajeev Jain, Andreas Wilke, Rylie Weaver, Alexander Partin
, Thomas S. Brettin, Rick Stevens:
An Automation Framework for Comparison of Cancer Response Models Across Configurations. e-Science 2023: 1-10 - [c2]Oleksandr Narykov, Yitan Zhu, Thomas S. Brettin, Yvonne A. Evrard, Alexander Partin, Maulik Shukla, Priyanka Vasanthakumari, James H. Doroshow, Rick Stevens:
Entropy-Based Regularization on Deep Learning Models for Anti-Cancer Drug Response Prediction. SC Workshops 2023: 121-122 - 2022
- [j2]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:
A cross-study analysis of drug response prediction in cancer cell lines. Briefings Bioinform. 23(1) (2022) - [i7]Alexander Partin, Thomas S. Brettin, Yitan Zhu, Oleksandr Narykov, Austin Clyde, Jamie C. Overbeek, Rick L. Stevens:
Deep learning methods for drug response prediction in cancer: predominant and emerging trends. CoRR abs/2211.10442 (2022) - 2021
- [j1]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:
Learning curves for drug response prediction in cancer cell lines. BMC Bioinform. 22(1): 252 (2021) - [c1]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:
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. ICPP 2021: 40:1-40:12 - [i6]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:
Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers. CoRR abs/2103.02843 (2021) - [i5]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:
Protein-Ligand Docking Surrogate Models: A SARS-CoV-2 Benchmark for Deep Learning Accelerated Virtual Screening. CoRR abs/2106.07036 (2021) - 2020
- [i4]Austin Clyde, Tom Brettin, Alexander Partin, Maulik Shaulik, Hyun Seung Yoo, Yvonne A. Evrard, Yitan Zhu, Fangfang Xia, Rick Stevens:
A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep Learning. CoRR abs/2005.00095 (2020) - [i3]Yitan Zhu, Thomas S. Brettin, Yvonne A. Evrard, Alexander Partin, Fangfang Xia, Maulik Shukla, Hyun Seung Yoo, James H. Doroshow, Rick Stevens:
Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response. CoRR abs/2005.09572 (2020) - [i2]Aymen Al Saadi, Dario Alfè, Yadu N. Babuji, Agastya Bhati, Ben Blaiszik, Thomas S. Brettin, Kyle Chard, Ryan Chard, Peter V. Coveney, Anda Trifan, Alex Brace, Austin Clyde, Ian T. Foster, Tom Gibbs, Shantenu Jha, Kristopher Keipert, Thorsten Kurth, Dieter Kranzlmüller, Hyungro Lee, Zhuozhao Li, Heng Ma, André Merzky, Gerald Mathias, Alexander Partin, Junqi Yin, Arvind Ramanathan, Ashka Shah, Abraham C. Stern, Rick Stevens, Li Tan, Mikhail Titov, Aristeidis Tsaris, Matteo Turilli, Huub J. J. Van Dam, Shunzhou Wan, David Wifling:
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. CoRR abs/2010.06574 (2020) - [i1]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 Stevens:
Learning Curves for Drug Response Prediction in Cancer Cell Lines. CoRR abs/2011.12466 (2020)
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