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ORCIDThomas S. Brettin
◁ ▶ joint publications with coauthor community group 1
- > Home > Persons > Thomas S. Brettin
Publications
- 2024
[c15]Archit Vasan, Ozan Gökdemir, Alexander Brace, Arvind Ramanathan, Thomas S. Brettin, Rick Stevens, Venkatram Vishwanath:
High Performance Binding Affinity Prediction with a Transformer-Based Surrogate Model. IPDPS (Workshops) 2024: 571-580- 2023
- [j16]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, Defne G. Ozgulbas, Natalia Vassilieva, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan:
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. 37(6): 683-705 (2023) - [j15]Robert D. Olson, Rida Assaf, Thomas S. Brettin, Neal Conrad, Clark Cucinell, James J. Davis, Donald M. Dempsey, Allan Dickerman, Emily M. Dietrich, Ronald W. Kenyon, Mehmet Kuscuoglu, Elliot J. Lefkowitz, Jian Lu, Dustin Machi, Catherine Macken, Chunhong Mao, Anna Maria Niewiadomska, Marcus Nguyen, Gary J. Olsen, Jamie C. Overbeek, Bruce D. Parrello, Victoria Parrello, Jacob s Porter, Gordon D. Pusch, Maulik Shukla, Indresh Singh, Lucy Stewart, Gene Tan, Chris Thomas, Margo VanOeffelen, Veronika Vonstein, Zachary S. Wallace, Andrew S. Warren, Alice R. Wattam, Fangfang Xia, Hyun Seung Yoo, Yun Zhang, Christian M. Zmasek, Richard H. Scheuermann, Rick L. Stevens:
Introducing the Bacterial and Viral Bioinformatics Resource Center (BV-BRC): a resource combining PATRIC, IRD and ViPR. Nucleic Acids Res. 51(D1): 678-689 (2023) - [c14]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 - [c13]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 - [c12]Archit Vasan, Thomas S. Brettin, Rick Stevens, Arvind Ramanathan, Venkatram Vishwanath:
Scalable Lead Prediction with Transformers using HPC resources. SC Workshops 2023: 123 - [i14]Rafael Vescovi, Tobias Ginsburg, Kyle Hippe, Doga Ozgulbas, Casey Stone, Abraham Stroka, Rory Butler, Ben Blaiszik, Tom Brettin, Kyle Chard, Mark Hereld, Arvind Ramanathan, Rick Stevens, Aikaterini Vriza, Jie Xu, Qingteng Zhang, Ian T. Foster:
Towards a Modular Architecture for Science Factories. CoRR abs/2308.09793 (2023) - [i13]Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens:
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR abs/2310.04610 (2023) - 2022
- [j14]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) - [j13]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, Darin Hauner, Vilmos Kertesz, Neeraj Kumar, Hyungro Lee, Zhuozhao Li, André Merzky, Jurgen G. Schmidt, Li Tan, Mikhail Titov, Anda Trifan, Matteo Turilli, Hubertus Van Dam, Srinivas C. Chennubhotla, Shantenu Jha, Andrey Kovalevsky, Arvind Ramanathan, Martha S. Head, Rick Stevens:
High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor. J. Chem. Inf. Model. 62(1): 116-128 (2022) - [c11]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, Rick L. Stevens, Peter Nugent, Daniel A. Jacobson, James B. Brown:
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery. ICLR 2022 - [i12]Alexander Partin, Thomas S. Brettin, Yitan Zhu, Oleksandr Narykov, Austin Clyde, Jamie Overbeek, Rick L. Stevens:
Deep learning methods for drug response prediction in cancer: predominant and emerging trends. CoRR abs/2211.10442 (2022) - 2021
- [j12]Margo VanOeffelen, Marcus Nguyen, Derya Aytan-Aktug, Thomas S. Brettin, Emily M. Dietrich, Ronald W. Kenyon, Dustin Machi, Chunhong Mao, Robert Olson, Gordon D. Pusch, Maulik Shukla, Rick Stevens, Veronika Vonstein, Andrew S. Warren, Alice R. Wattam, Hyun Seung Yoo, James J. Davis:
A genomic data resource for predicting antimicrobial resistance from laboratory-derived antimicrobial susceptibility phenotypes. Briefings Bioinform. 22(6) (2021) - [j11]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) - [c10]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 - [i11]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) - [i10]Yulun Wu, Nicholas Choma, Andrew Deru Chen, Mikaela Cashman, Érica T. Prates, Manesh Shah, Verónica G. Melesse Vergara, Austin Clyde, Thomas S. Brettin, Wibe A. de Jong, Neeraj Kumar, Martha S. Head, Rick L. Stevens, Peter Nugent, Daniel A. Jacobson, James B. Brown:
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery. CoRR abs/2106.02190 (2021) - [i9]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) - [i8]Max Zvyagin, Thomas S. Brettin, Arvind Ramanathan, Sumit Kumar Jha:
CrossedWires: A Dataset of Syntactically Equivalent but Semantically Disparate Deep Learning Models. CoRR abs/2108.12768 (2021) - 2020
- [j10]James J. Davis, Alice R. Wattam, Ramy K. Aziz, Thomas S. Brettin, Ralph Butler, Rory Butler, Philippe Chlenski, Neal Conrad, Allan Dickerman, Emily M. Dietrich, Joseph L. Gabbard, Svetlana Gerdes, Andrew Guard, Ronald W. Kenyon, Dustin Machi, Chunhong Mao, Daniel E. Murphy-Olson, Marcus Nguyen, Eric K. Nordberg, Gary J. Olsen, Robert Olson, Jamie C. Overbeek, Ross A. Overbeek, Bruce D. Parrello, Gordon D. Pusch, Maulik Shukla, Chris Thomas, Margo VanOeffelen, Veronika Vonstein, Andrew S. Warren, Fangfang Xia, Dawen Xie, Hyun Seung Yoo, Rick Stevens:
The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities. Nucleic Acids Res. 48(Database-Issue): D606-D612 (2020) - [c9]Justin M. Wozniak, Hyun Seung Yoo, Jamaludin Mohd-Yusof, Bogdan Nicolae, Nicholson T. Collier, Jonathan Ozik, Thomas S. Brettin, Rick Stevens:
High-bypass Learning: Automated Detection of Tumor Cells That Significantly Impact Drug Response. MLHPC/AI4S@SC 2020: 40-49 - [i7]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) - [i6]Neil Getty, Thomas S. Brettin, Dong Jin, Rick Stevens, Fangfang Xia:
Deep Medical Image Analysis with Representation Learning and Neuromorphic Computing. CoRR abs/2005.05431 (2020) - [i5]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) - [i4]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, Yi Ren, Nicholaus Saint, Marcus Schwarting, Rick Stevens, Hubertus Van Dam, Rick Wagner:
Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release. CoRR abs/2006.02431 (2020) - [i3]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) - [i2]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) - 2019
- [j9]Dionysios A. Antonopoulos, Rida Assaf, Ramy Karam Aziz, Thomas S. Brettin, Christopher Bun, Neal Conrad, James J. Davis, Emily M. Dietrich, Terry Disz, Svetlana Gerdes, Ronald W. Kenyon, Dustin Machi, Chunhong Mao, Daniel E. Murphy-Olson, Eric K. Nordberg, Gary J. Olsen, Robert Olson, Ross A. Overbeek, Bruce D. Parrello, Gordon D. Pusch, John Santerre, Maulik Shukla, Rick L. Stevens, Margo VanOeffelen, Veronika Vonstein, Andrew S. Warren, Alice R. Wattam, Fangfang Xia, Hyun Seung Yoo:
PATRIC as a unique resource for studying antimicrobial resistance. Briefings Bioinform. 20(4): 1094-1102 (2019) - [c8]Xingfu Wu, Valerie E. Taylor, Justin M. Wozniak, Rick Stevens, Thomas S. Brettin, Fangfang Xia:
Performance, Energy, and Scalability Analysis and Improvement of Parallel Cancer Deep Learning CANDLE Benchmarks. ICPP 2019: 78:1-78:11 - [c7]Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan M. Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens:
Scalable reinforcement-learning-based neural architecture search for cancer deep learning research. SC 2019: 37:1-37:33 - [i1]Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan M. Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens:
Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research. CoRR abs/1909.00311 (2019) - 2018
- [j8]Justin M. Wozniak, Rajeev Jain, Prasanna Balaprakash, Jonathan Ozik, Nicholson T. Collier, John Bauer, Fangfang Xia, Thomas S. Brettin, Rick Stevens, Jamaludin Mohd-Yusof, Cristina Garcia-Cardona, Brian Van Essen, Matthew Baughman:
CANDLE/Supervisor: a workflow framework for machine learning applied to cancer research. BMC Bioinform. 19-S(18): 59-69 (2018) - [j7]Fangfang Xia, Maulik Shukla, Thomas S. Brettin, Cristina Garcia-Cardona, Judith D. Cohn, Jonathan E. Allen, Sergei Maslov, Susan L. Holbeck, James H. Doroshow, Yvonne A. Evrard, Eric A. Stahlberg, Rick L. Stevens:
Predicting tumor cell line response to drug pairs with deep learning. BMC Bioinform. 19-S(18): 71-79 (2018) - [c6]George F. Zaki, Justin M. Wozniak, Jonathan Ozik, Nicholson T. Collier, Thomas S. Brettin, Rick Stevens:
Portable and Reusable Deep Learning Infrastructure with Containers to Accelerate Cancer Studies. ESPM2@SC 2018: 54-61 - 2017
- [j6]Alice R. Wattam, James J. Davis, Rida Assaf, Sébastien Boisvert, Thomas S. Brettin, Christopher Bun, Neal Conrad, Emily M. Dietrich, Terry Disz, Joseph L. Gabbard, Svetlana Gerdes, Christopher S. Henry, Ronald W. Kenyon, Dustin Machi, Chunhong Mao, Eric K. Nordberg, Gary J. Olsen, Daniel E. Murphy-Olson, Robert Olson, Ross A. Overbeek, Bruce D. Parrello, Gordon D. Pusch, Maulik Shukla, Veronika Vonstein, Andrew S. Warren, Fangfang Xia, Hyun Seung Yoo, Rick L. Stevens:
Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center. Nucleic Acids Res. 45(Database-Issue): D535-D542 (2017) - [c5]Jessica A. Boten, Donna R. Rivera, Madhumita Myneni, Georgia D. Tourassi, Tanmoy Bhattacharya, Ana Paula de Oliveira Sales, Thomas S. Brettin, Paul A. Fearn, Lynne Penberthy:
Leveraging Large-Scale Computing for Population Information Integration, Analysis, and Modeling. AMIA 2017 - 2015
- [j5]Andreas Wilke, Jared Bischof, Travis Harrison, Tom Brettin, Mark D'Souza, Wolfgang Gerlach, Hunter Matthews, Tobias Paczian, Jared Wilkening, Elizabeth M. Glass, Narayan Desai, Folker Meyer:
A RESTful API for Accessing Microbial Community Data for MG-RAST. PLoS Comput. Biol. 11(1) (2015) - 2012
- [j4]Pavel S. Novichkov, Thomas S. Brettin, Elena S. Novichkova, Paramvir S. Dehal, Adam P. Arkin, Inna Dubchak, Dmitry A. Rodionov:
RegPrecise web services interface: programmatic access to the transcriptional regulatory interactions in bacteria reconstructed by comparative genomics. Nucleic Acids Res. 40(Web-Server-Issue): 604-608 (2012) - 2011
- [j3]Shelton D. Griffith, Daniel Quest, Thomas S. Brettin, Robert W. Cottingham:
Scenario driven data modelling: a method for integrating diverse sources of data and data streams. BMC Bioinform. 12(S-10): S17 (2011) - [c4]Thomas S. Brettin, Laura Pullum, Daniel Quest, Xiaohui Cui, Songhua Xu, Richard Stouder:
Poster: a novel architecture for biothreat situation awareness. SC Companion 2011: 45-46 - 2010
- [j2]Daniel Quest, Miriam L. Land, Thomas S. Brettin, Robert W. Cottingham:
Next generation models for storage and representation of microbial biological annotation. BMC Bioinform. 11(S-6): S15 (2010) - 2001
- [j1]Michael E. Wall, Patricia A. Dyck, Thomas S. Brettin:
SVDMAN-singular value decomposition analysis of microarray data. Bioinform. 17(6): 566-568 (2001)
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