Jonathan E. Allen

27 papers A 1B 1Journal 23Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	SurGBSA: Learning Representations From Molecular Dynamics Simulations. CoRR Derek Jones, Yue Yang, Felice C. Lightstone, Niema Moshiri, Jonathan E. Allen, Tajana Simunic Rosing
2024	J	`jnl`	Enhancing Docking Accuracy with PECAN2, a 3D Atomic Neural Network Trained without Co-Complex Crystal Structures. Mach. Learn. Knowl. Extr. Heesung Shim, Jonathan E. Allen, W. F. Drew Bennett
2024	J	`jnl`	GENTANGLE: integrated computational design of gene entanglements. Bioinform. Jose Manuel Martí, Chloe Hsu, Charlotte Rochereau, Chenling Xu, Tomasz Blazejewski, Hunter Nisonoff, Sean P. Leonard, Christina S. Kang-Yun, Jennifer Chlebek, Dante P. Ricci, Dan Park, Harris Wang, Jennifer Listgarten, Yongqin Jiao, Jonathan E. Allen
2023	J	`jnl`	Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method. J. Chem. Inf. Model. 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
2023	J	`jnl`	HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations. CoRR Derek Jones, Jonathan E. Allen, Xiaohua Zhang, Behnam Khaleghi, Jaeyoung Kang, Weihong Xu, Niema Moshiri, Tajana Simunic Rosing
2022	J	`jnl`	A cross-study analysis of drug response prediction in cancer cell lines. Briefings Bioinform. 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
2022	J	`jnl`	Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery. CoRR Ya Ju Fan, Jonathan E. Allen, Kevin S. McLoughlin, Da Shi, Brian J. Bennion, Xiaohua Zhang, Felice C. Lightstone
2022	J	`jnl`	MACAW: An Accessible Tool for Molecular Embedding and Inverse Molecular Design. J. Chem. Inf. Model. Vincent Blay, Tijana Radivojevic, Jonathan E. Allen, Corey M. Hudson, Héctor García Martín
2022	J	`jnl`	Pose Classification Using Three-Dimensional Atomic Structure-Based Neural Networks Applied to Ion Channel-Ligand Docking. J. Chem. Inf. Model. Heesung Shim, Hyojin Kim, Jonathan E. Allen, Heike Wulff
2022	B	`conf`	Scalable Composition and Analysis Techniques for Massive Scientific Workflows. e-Science 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
2021	J	`jnl`	Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models. Int. J. High Perform. Comput. Appl. 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
2021	J	`jnl`	High-Throughput Virtual Screening of Small Molecule Inhibitors for SARS-CoV-2 Protein Targets with Deep Fusion Models. CoRR 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
2021	A	`conf`	High-throughput virtual screening of small molecule inhibitors for SARS-CoV-2 protein targets with deep fusion models. SC 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
2021	J	`jnl`	Improved Protein-Ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference. J. Chem. Inf. Model. 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
2021	J	`jnl`	Machine Learning Models to Predict Inhibition of the Bile Salt Export Pump. J. Chem. Inf. Model. 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
2020	J	`jnl`	AMPL: A Data-Driven Modeling Pipeline for Drug Discovery. J. Chem. Inf. Model. 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
2020	J	`jnl`	Binding Affinity Prediction by Pairwise Function Based on Neural Network. J. Chem. Inf. Model. Fangqiang Zhu, Xiaohua Zhang, Jonathan E. Allen, Derek Jones, Felice C. Lightstone
2020	J	`jnl`	Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference. CoRR 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
2020	J	`jnl`	Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning. J. Chem. Inf. Model. W. F. Drew Bennett, Stewart He, Camille L. Bilodeau, Derek Jones, Delin Sun, Hyojin Kim, Jonathan E. Allen, Felice C. Lightstone, Helgi I. Ingólfsson
2020	—	`conf`	Quantifying Overfitting Potential in Drug Binding Datasets. ICCS (3) Brian Davis, Kevin McLoughlin, Jonathan E. Allen, Sally R. Ellingson
2019	J	`jnl`	AMPL: A Data-Driven Modeling Pipeline for Drug Discovery. CoRR 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
2019	J	`jnl`	Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency. CoRR Ya Ju Fan, Jonathan E. Allen, Sam Ade Jacobs, Brian C. Van Essen
2018	J	`jnl`	Predicting tumor cell line response to drug pairs with deep learning. BMC Bioinform. 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
2014	—	`conf`	Design and Optimization of a Metagenomics Analysis Workflow for NVRAM. IPDPS Workshops Sasha Ames, Jonathan E. Allen, David A. Hysom, G. Scott Lloyd, Maya B. Gokhale
2013	J	`jnl`	Scalable metagenomic taxonomy classification using a reference genome database. Bioinform. Sasha Ames, David A. Hysom, Shea N. Gardner, G. Scott Lloyd, Maya B. Gokhale, Jonathan E. Allen
2006	J	`jnl`	A phylogenetic generalized hidden Markov model for predicting alternatively spliced exons. Algorithms Mol. Biol. Jonathan E. Allen, Steven L. Salzberg
2005	J	`jnl`	JIGSAW: integration of multiple sources of evidence for gene prediction. Bioinform. Jonathan E. Allen, Steven Salzberg