Jonathan E. Allen

Orcid: 0000-0002-4359-8263

According to our database¹, Jonathan E. Allen authored at least 22 papers between 2005 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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PhD thesis

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Bibliography

2023

Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., November, 2023

HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations.

[BibT_eX]

[DOI]

Tajana Simunic Rosing

CoRR, 2023

2022

Pose Classification Using Three-Dimensional Atomic Structure-Based Neural Networks Applied to Ion Channel-Ligand Docking.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2022

MACAW: An Accessible Tool for Molecular Embedding and Inverse Molecular Design.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2022

Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery.

[BibT_eX]

[DOI]

CoRR, 2022

A cross-study analysis of drug response prediction in cancer cell lines.

[BibT_eX]

[DOI]

Briefings Bioinform., 2022

Scalable Composition and Analysis Techniques for Massive Scientific Workflows.

[BibT_eX]

[DOI]

Bronis R. de Supinski

Brian Van Essen

Jonathan E. Allen

Felice C. Lightstone

Proceedings of the 18th IEEE International Conference on e-Science, 2022

2021

Machine Learning Models to Predict Inhibition of the Bile Salt Export Pump.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2021

Improved Protein-Ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2021

Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models.

[BibT_eX]

[DOI]

Int. J. High Perform. Comput. Appl., 2021

High-throughput virtual screening of small molecule inhibitors for SARS-CoV-2 protein targets with deep fusion models.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2021

2020

Binding Affinity Prediction by Pairwise Function Based on Neural Network.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2020

AMPL: A Data-Driven Modeling Pipeline for Drug Discovery.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2020

Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2020

Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference.

[BibT_eX]

[DOI]

CoRR, 2020

Quantifying Overfitting Potential in Drug Binding Datasets.

[BibT_eX]

[DOI]

Proceedings of the Computational Science - ICCS 2020, 2020

2019

Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Predicting tumor cell line response to drug pairs with deep learning.

[BibT_eX]

[DOI]

Fangfang Xia

Maulik Shukla

Thomas S. Brettin

Cristina Garcia-Cardona

BMC Bioinform., 2018

2014

Design and Optimization of a Metagenomics Analysis Workflow for NVRAM.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014

2013

Scalable metagenomic taxonomy classification using a reference genome database.

[BibT_eX]

[DOI]

Bioinform., 2013

2006

A phylogenetic generalized hidden Markov model for predicting alternatively spliced exons.

[BibT_eX]

[DOI]

Jonathan E. Allen

Steven L. Salzberg

Algorithms Mol. Biol., 2006

2005

JIGSAW: integration of multiple sources of evidence for gene prediction.

[BibT_eX]

[DOI]

Jonathan E. Allen

Steven Salzberg

Bioinform., 2005

Jonathan E. Allen

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