Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Jonathan E. Allen

Jonathan E. Allen
Alert button

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


Mar 27, 2023
Derek Jones, Jonathan E. Allen, Xiaohua Zhang, Behnam Khaleghi, Jaeyoung Kang, Weihong Xu, Niema Moshiri, Tajana S. Rosing

Add code
Alert button

Figure 1 for HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations
Figure 2 for HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations
Figure 3 for HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations
Figure 4 for HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery


Oct 31, 2022
Ya Ju Fan, Jonathan E. Allen, Kevin S. McLoughlin, Da Shi, Brian J. Bennion, Xiaohua Zhang, Felice C. Lightstone

Add code
Alert button

Figure 1 for Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery
Figure 2 for Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery
Figure 3 for Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery
Figure 4 for Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

High-Throughput Virtual Screening of Small Molecule Inhibitors for SARS-CoV-2 Protein Targets with Deep Fusion Models


Apr 09, 2021
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 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 Wong, Yue Yang, Adam Zemla, Xiaohua Zhang, Fangqiang Zhu, Felice C. Lightstone, Jonathan E. Allen

Add code
Alert button

Figure 1 for High-Throughput Virtual Screening of Small Molecule Inhibitors for SARS-CoV-2 Protein Targets with Deep Fusion Models
Figure 2 for High-Throughput Virtual Screening of Small Molecule Inhibitors for SARS-CoV-2 Protein Targets with Deep Fusion Models
Figure 3 for High-Throughput Virtual Screening of Small Molecule Inhibitors for SARS-CoV-2 Protein Targets with Deep Fusion Models
Figure 4 for High-Throughput Virtual Screening of Small Molecule Inhibitors for SARS-CoV-2 Protein Targets with Deep Fusion Models

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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


May 17, 2020
Derek Jones, Hyojin Kim, Xiaohua Zhang, Adam Zemla, Garrett Stevenson, William D. Bennett, Dan Kirshner, Sergio Wong, Felice Lightstone, Jonathan E. Allen

Add code
Alert button

Figure 1 for Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference
Figure 2 for Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference
Figure 3 for Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference
Figure 4 for Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

AMPL: A Data-Driven Modeling Pipeline for Drug Discovery


Nov 14, 2019
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

Add code
Alert button

Figure 1 for AMPL: A Data-Driven Modeling Pipeline for Drug Discovery
Figure 2 for AMPL: A Data-Driven Modeling Pipeline for Drug Discovery
Figure 3 for AMPL: A Data-Driven Modeling Pipeline for Drug Discovery
Figure 4 for AMPL: A Data-Driven Modeling Pipeline for Drug Discovery

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency


Jan 30, 2019
Ya Ju Fan, Jonathan E. Allen, Sam Ade Jacobs, Brian C. Van Essen

Add code
Alert button

Figure 1 for Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency
Figure 2 for Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency
Figure 3 for Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency
Figure 4 for Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency
* Second Workshop on HPC Applications in Precision Medicine, June 2018 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email