JIGSAW: integration of multiple sources of evidence for gene prediction. - Jonathan E. Allen; Steven Salzberg (Bioinform., 2005)

A phylogenetic generalized hidden Markov model for predicting alternatively spliced exons. - Jonathan E. Allen; Steven L. Salzberg (Algorithms Mol. Biol., 2006)

Scalable metagenomic taxonomy classification using a reference genome database. - Sasha Ames; David A. Hysom; Shea N. Gardner; G. Scott Lloyd; Maya B. Gokhale; Jonathan E. Allen (Bioinform., 2013)

Design and Optimization of a Metagenomics Analysis Workflow for NVRAM. - Sasha Ames; Jonathan E. Allen; David A. Hysom; G. Scott Lloyd; Maya B. Gokhale (IPDPS Workshops, 2014)

Predicting tumor cell line response to drug pairs with deep learning. - 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 (BMC Bioinform., 2018)

Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency. - Ya Ju Fan; Jonathan E. Allen; Sam Ade Jacobs; Brian C. Van Essen (CoRR, 2019)

Quantifying Overfitting Potential in Drug Binding Datasets. - Brian Davis; Kevin McLoughlin; Jonathan E. Allen; Sally R. Ellingson (ICCS (3), 2020)

Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference. - Derek Jones; Hyojin Kim 001; Xiaohua Zhang; Adam T. Zemla; Garrett Stevenson; William D. Bennett; Dan Kirshner 001; Sergio Ernesto Wong; Felice C. Lightstone; Jonathan E. Allen (CoRR, 2020)

Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning. - W. F. Drew Bennett; Stewart He; Camille L. Bilodeau; Derek Jones; Delin Sun; Hyojin Kim 001; Jonathan E. Allen; Felice C. Lightstone; Helgi I. Ingólfsson (J. Chem. Inf. Model., 2020)

AMPL: A Data-Driven Modeling Pipeline for Drug Discovery. - 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 (J. Chem. Inf. Model., 2020)

Binding Affinity Prediction by Pairwise Function Based on Neural Network. - Fangqiang Zhu; Xiaohua Zhang; Jonathan E. Allen; Derek Jones; Felice C. Lightstone (J. Chem. Inf. Model., 2020)

High-throughput virtual screening of small molecule inhibitors for SARS-CoV-2 protein targets with deep fusion models. - Garrett A. Stevenson; Derek Jones; Hyojin Kim 001; W. F. Drew Bennett; Brian J. Bennion; Monica Borucki; Feliza Bourguet; Aidan Epstein; Magdalena Franco; Brooke Harmon; Stewart He; Max P. Katz; et al. (SC, 2021)

Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models. - 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 (Int. J. High Perform. Comput. Appl., 2021)

Improved Protein-Ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference. - Derek Jones; Hyojin Kim 001; Xiaohua Zhang; Adam T. Zemla; Garrett Stevenson; W. F. Drew Bennett; Daniel A. Kirshner; Sergio Ernesto Wong; Felice C. Lightstone; Jonathan E. Allen (J. Chem. Inf. Model., 2021)

Machine Learning Models to Predict Inhibition of the Bile Salt Export Pump. - 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 (J. Chem. Inf. Model., 2021)

Scalable Composition and Analysis Techniques for Massive Scientific Workflows. - Dong H. Ahn; Xiaohua Zhang; Jeffrey Mast; Stephen Herbein; Francesco Di Natale; Dan Kirshner 001; Sam Ade Jacobs; Ian Karlin; Daniel J. Milroy; Bronis R. de Supinski; Brian Van Essen; Jonathan E. Allen; et al. (e-Science, 2022)

A cross-study analysis of drug response prediction in cancer cell lines. - 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; et al. (Briefings Bioinform., 2022)

Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery. - Ya Ju Fan; Jonathan E. Allen; Kevin S. McLoughlin; Da Shi; Brian J. Bennion; Xiaohua Zhang; Felice C. Lightstone (CoRR, 2022)

MACAW: An Accessible Tool for Molecular Embedding and Inverse Molecular Design. - Vincent Blay; Tijana Radivojevic; Jonathan E. Allen; Corey M. Hudson; Héctor García Martín (J. Chem. Inf. Model., 2022)

Pose Classification Using Three-Dimensional Atomic Structure-Based Neural Networks Applied to Ion Channel-Ligand Docking. - Heesung Shim; Hyojin Kim 001; Jonathan E. Allen; Heike Wulff (J. Chem. Inf. Model., 2022)

HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations. - Derek Jones; Jonathan E. Allen; Xiaohua Zhang; Behnam Khaleghi; Jaeyoung Kang 001; Weihong Xu; Niema Moshiri; Tajana Simunic Rosing (CoRR, 2023)

Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method. - Garrett A. Stevenson; Dan Kirshner 001; Brian J. Bennion; Yue Yang; Xiaohua Zhang; Adam T. Zemla; Marisa W. Torres; Aidan Epstein; Derek Jones; Hyojin Kim 001; W. F. Drew Bennett; Sergio Ernesto Wong; et al. (J. Chem. Inf. Model., 2023)

Enhancing Docking Accuracy with PECAN2, a 3D Atomic Neural Network Trained without Co-Complex Crystal Structures. - Heesung Shim; Jonathan E. Allen; W. F. Drew Bennett (Mach. Learn. Knowl. Extr., 2024)