Zobrazeno 1 - 10
of 204
pro vyhledávání: '"Allen, Jonathan E"'
HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations
Autor:
Jones, Derek, Allen, Jonathan E., Zhang, Xiaohua, Khaleghi, Behnam, Kang, Jaeyoung, Xu, Weihong, Moshiri, Niema, Rosing, Tajana S.
Publicly available collections of drug-like molecules have grown to comprise 10s of billions of possibilities in recent history due to advances in chemical synthesis. Traditional methods for identifying ``hit'' molecules from a large collection of po
Externí odkaz:
http://arxiv.org/abs/2303.15604
Autor:
Fan, Ya Ju, Allen, Jonathan E., McLoughlin, Kevin S., Shi, Da, Bennion, Brian J., Zhang, Xiaohua, Lightstone, Felice C.
Neural Network (NN) models provide potential to speed up the drug discovery process and reduce its failure rates. The success of NN models require uncertainty quantification (UQ) as drug discovery explores chemical space beyond the training data dist
Externí odkaz:
http://arxiv.org/abs/2210.17043
Autor:
Stevenson, Garrett A., Jones, Derek, Kim, Hyojin, Bennett, W. F. Drew, Bennion, Brian J., Borucki, Monica, Bourguet, Feliza, Epstein, Aidan, Franco, Magdalena, Harmon, Brooke, He, Stewart, Katz, Max P., Kirshner, Daniel, Lao, Victoria, Lau, Edmond Y., Lo, Jacky, McLoughlin, Kevin, Mosesso, Richard, Murugesh, Deepa K., Negrete, Oscar A., Saada, Edwin A., Segelke, Brent, Stefan, Maxwell, Torres, Marisa W., Weilhammer, Dina, Wong, Sergio, Yang, Yue, Zemla, Adam, Zhang, Xiaohua, Zhu, Fangqiang, Lightstone, Felice C., Allen, Jonathan E.
Structure-based Deep Fusion models were recently shown to outperform several physics- and machine learning-based protein-ligand binding affinity prediction methods. As part of a multi-institutional COVID-19 pandemic response, over 500 million small m
Externí odkaz:
http://arxiv.org/abs/2104.04547
Autor:
Jones, Derek, Kim, Hyojin, Zhang, Xiaohua, Zemla, Adam, Stevenson, Garrett, Bennett, William D., Kirshner, Dan, Wong, Sergio, Lightstone, Felice, Allen, Jonathan E.
Predicting accurate protein-ligand binding affinity is important in drug discovery but remains a challenge even with computationally expensive biophysics-based energy scoring methods and state-of-the-art deep learning approaches. Despite the recent a
Externí odkaz:
http://arxiv.org/abs/2005.07704
Autor:
McLoughlin, Kevin S., Jeong, Claire G., Sweitzer, Thomas D., Minnich, Amanda J., Tse, Margaret J., Bennion, Brian J., Allen, Jonathan E., Calad-Thomson, Stacie, Rush, Thomas S., Brase, James M.
Drug-induced liver injury (DILI) is the most common cause of acute liver failure and a frequent reason for withdrawal of candidate drugs during preclinical and clinical testing. An important type of DILI is cholestatic liver injury, caused by buildup
Externí odkaz:
http://arxiv.org/abs/2002.12541
Akademický článek
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Autor:
Minnich, Amanda J., McLoughlin, Kevin, Tse, Margaret, Deng, Jason, Weber, Andrew, Murad, Neha, Madej, Benjamin D., Ramsundar, Bharath, Rush, Tom, Calad-Thomson, Stacie, Brase, Jim, Allen, Jonathan E.
One of the key requirements for incorporating machine learning into the drug discovery process is complete reproducibility and traceability of the model building and evaluation process. With this in mind, we have developed an end-to-end modular and e
Externí odkaz:
http://arxiv.org/abs/1911.05211
Gene expression profiles have been widely used to characterize patterns of cellular responses to diseases. As data becomes available, scalable learning toolkits become essential to processing large datasets using deep learning models to model complex
Externí odkaz:
http://arxiv.org/abs/1901.11152
Autor:
Fan, Ya Ju, Allen, Jonathan E., McLoughlin, Kevin S., Shi, Da, Bennion, Brian J., Zhang, Xiaohua, Lightstone, Felice C.
Publikováno v:
In Artificial Intelligence Chemistry June 2023 1(1)
Akademický článek
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