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ORCIDJonathan E. Allen
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- Jonathan Aellen
- Jonathan Allen
- Jonathan P. Allen — University of San Francisco, School of Management, San Francisco, CA, USA
- Jonathan Parkes Allen
- Jonathan R. C. Allen
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2020 – today
- 2024
[j15]Heesung Shim
, Jonathan E. Allen, W. F. Drew Bennett:
Enhancing Docking Accuracy with PECAN2, a 3D Atomic Neural Network Trained without Co-Complex Crystal Structures. Mach. Learn. Knowl. Extr. 6(1): 642-657 (2024)- 2023
- [j14]Garrett A. Stevenson, Dan Kirshner, Brian J. Bennion, Yue Yang, Xiaohua Zhang, Adam T. Zemla, Marisa W. Torres, Aidan Epstein, Derek Jones, Hyojin Kim, W. F. Drew Bennett, Sergio Ernesto Wong, Jonathan E. Allen, Felice C. Lightstone:
Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method. J. Chem. Inf. Model. 63(21): 6655-6666 (2023) - [i6]Derek Jones, Jonathan E. Allen, Xiaohua Zhang, Behnam Khaleghi, Jaeyoung Kang, Weihong Xu, Niema Moshiri, Tajana Simunic Rosing:
HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations. CoRR abs/2303.15604 (2023) - 2022
- [j13]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) - [j12]Heesung Shim, Hyojin Kim, Jonathan E. Allen, Heike Wulff:
Pose Classification Using Three-Dimensional Atomic Structure-Based Neural Networks Applied to Ion Channel-Ligand Docking. J. Chem. Inf. Model. 62(10): 2301-2315 (2022) - [j11]Vincent Blay, Tijana Radivojevic, Jonathan E. Allen, Corey M. Hudson, Héctor García Martín:
MACAW: An Accessible Tool for Molecular Embedding and Inverse Molecular Design. J. Chem. Inf. Model. 62(15): 3551-3564 (2022) - [c4]Dong H. Ahn, Xiaohua Zhang, Jeffrey Mast, Stephen Herbein, Francesco Di Natale, Dan Kirshner, Sam Ade Jacobs, Ian Karlin, Daniel J. Milroy, Bronis R. de Supinski, Brian Van Essen, Jonathan E. Allen, Felice C. Lightstone:
Scalable Composition and Analysis Techniques for Massive Scientific Workflows. e-Science 2022: 32-43 - [i5]Ya Ju Fan, Jonathan E. Allen, Kevin S. McLoughlin, Da Shi, Brian J. Bennion, Xiaohua Zhang, Felice C. Lightstone:
Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery. CoRR abs/2210.17043 (2022) - 2021
- [j10]Sam Ade Jacobs, Tim Moon, Kevin McLoughlin, Derek Jones, David Hysom, Dong H. Ahn, John C. Gyllenhaal, Pythagoras Watson, Felice C. Lightstone, Jonathan E. Allen, Ian Karlin, Brian Van Essen:
Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models. Int. J. High Perform. Comput. Appl. 35(5) (2021) - [j9]Kevin McLoughlin, Claire G. Jeong, Thomas D. Sweitzer, Amanda J. Minnich, Margaret Tse, Brian J. Bennion, Jonathan E. Allen, Stacie Calad-Thomson, Tom Rush, Jim Brase:
Machine Learning Models to Predict Inhibition of the Bile Salt Export Pump. J. Chem. Inf. Model. 61(2): 587-602 (2021) - [j8]Derek Jones, Hyojin Kim, Xiaohua Zhang, Adam T. Zemla, Garrett Stevenson, W. F. Drew Bennett, Daniel A. Kirshner, Sergio Ernesto Wong, Felice C. Lightstone, Jonathan E. Allen:
Improved Protein-Ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference. J. Chem. Inf. Model. 61(4): 1583-1592 (2021) - [c3]Garrett A. Stevenson, Derek Jones, Hyojin Kim, W. F. Drew Bennett, Brian J. Bennion, Monica Borucki, Feliza Bourguet, Aidan Epstein, Magdalena Franco, Brooke Harmon, Stewart He, Max P. Katz, Daniel A. Kirshner, Victoria Lao, Edmond Y. Lau, Jacky Lo, Kevin McLoughlin, Richard Mosesso, Deepa K. Murugesh, Oscar A. Negrete, Edwin A. Saada, Brent Segelke, Maxwell Stefan, Marisa W. Torres, Dina Weilhammer, Sergio Ernesto Wong, Yue Yang, Adam T. Zemla, Xiaohua Zhang, Fangqiang Zhu, Felice C. Lightstone, Jonathan E. Allen:
High-throughput virtual screening of small molecule inhibitors for SARS-CoV-2 protein targets with deep fusion models. SC 2021: 74 - [i4]Garrett A. Stevenson, Derek Jones, Hyojin Kim, W. F. Drew Bennett, Brian J. Bennion, Monica Borucki, Feliza Bourguet, Aidan Epstein, Magdalena Franco, Brooke Harmon, Stewart He, Max P. Katz, Daniel A. Kirshner, Victoria Lao, Edmond Y. Lau, Jacky Lo, Kevin McLoughlin, Richard Mosesso, Deepa K. Murugesh, Oscar A. Negrete, Edwin A. Saada, Brent Segelke, Maxwell Stefan, Marisa W. Torres, Dina Weilhammer, Sergio Ernesto Wong, Yue Yang, Adam T. Zemla, Xiaohua Zhang, Fangqiang Zhu, Felice C. Lightstone, Jonathan E. Allen:
High-Throughput Virtual Screening of Small Molecule Inhibitors for SARS-CoV-2 Protein Targets with Deep Fusion Models. CoRR abs/2104.04547 (2021) - 2020
- [j7]Amanda J. Minnich, Kevin McLoughlin, Margaret Tse, Jason Deng, Andrew Weber, Neha Murad, Benjamin D. Madej, Bharath Ramsundar, Tom Rush, Stacie Calad-Thomson, Jim Brase, Jonathan E. Allen:
AMPL: A Data-Driven Modeling Pipeline for Drug Discovery. J. Chem. Inf. Model. 60(4): 1955-1968 (2020) - [j6]Fangqiang Zhu, Xiaohua Zhang, Jonathan E. Allen, Derek Jones, Felice C. Lightstone:
Binding Affinity Prediction by Pairwise Function Based on Neural Network. J. Chem. Inf. Model. 60(6): 2766-2772 (2020) - [j5]W. F. Drew Bennett, Stewart He, Camille L. Bilodeau, Derek Jones, Delin Sun, Hyojin Kim, Jonathan E. Allen, Felice C. Lightstone, Helgi I. Ingólfsson:
Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning. J. Chem. Inf. Model. 60(11): 5375-5381 (2020) - [c2]Brian Davis, Kevin McLoughlin, Jonathan E. Allen, Sally R. Ellingson:
Quantifying Overfitting Potential in Drug Binding Datasets. ICCS (3) 2020: 585-598 - [i3]Derek Jones, Hyojin Kim, Xiaohua Zhang, Adam T. Zemla, Garrett Stevenson, William D. Bennett, Dan Kirshner, Sergio Ernesto Wong, Felice C. Lightstone, Jonathan E. Allen:
Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference. CoRR abs/2005.07704 (2020)
2010 – 2019
- 2019
- [i2]Ya Ju Fan, Jonathan E. Allen, Sam Ade Jacobs, Brian C. Van Essen:
Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency. CoRR abs/1901.11152 (2019) - [i1]Amanda J. Minnich, Kevin McLoughlin, Margaret Tse, Jason Deng, Andrew Weber, Neha Murad, Benjamin D. Madej, Bharath Ramsundar, Tom Rush, Stacie Calad-Thomson, Jim Brase, Jonathan E. Allen:
AMPL: A Data-Driven Modeling Pipeline for Drug Discovery. CoRR abs/1911.05211 (2019) - 2018
- [j4]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) - 2014
- [c1]Sasha Ames, Jonathan E. Allen, David A. Hysom, G. Scott Lloyd, Maya B. Gokhale:
Design and Optimization of a Metagenomics Analysis Workflow for NVRAM. IPDPS Workshops 2014: 556-565 - 2013
- [j3]Sasha Ames, David A. Hysom, Shea N. Gardner, G. Scott Lloyd, Maya B. Gokhale, Jonathan E. Allen:
Scalable metagenomic taxonomy classification using a reference genome database. Bioinform. 29(18): 2253-2260 (2013)
2000 – 2009
- 2006
- [j2]Jonathan E. Allen, Steven L. Salzberg:
A phylogenetic generalized hidden Markov model for predicting alternatively spliced exons. Algorithms Mol. Biol. 1 (2006) - 2005
- [j1]Jonathan E. Allen, Steven Salzberg:
JIGSAW: integration of multiple sources of evidence for gene prediction. Bioinform. 21(18): 3596-3603 (2005)
Coauthor Index
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