David Ryan Koes

According to our database, David Ryan Koes authored at least 39 papers between 2001 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Open-ComBind: harnessing unlabeled data for improved binding pose prediction.

Andrew T. McNutt, David Ryan Koes

J. Comput. Aided Mol. Des., December, 2024

BigBind: Learning from Nonstructural Data for Structure-Based Virtual Screening.

Michael Brocidiacono, Paul G. Francoeur, Rishal Aggarwal, Konstantin I. Popov, David Ryan Koes, Alexander Tropsha

J. Chem. Inf. Model., 2024

CENsible: Interpretable Insights into Small-Molecule Binding with Context Explanation Networks.

Roshni Bhatt, David Ryan Koes, Jacob D. Durrant

J. Chem. Inf. Model., 2024

Mixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generation.

Ian Dunn, David Ryan Koes

CoRR, 2024

2023

Systematic Comparison of Experimental Crystallographic Geometries and Gas-Phase Computed Conformers for Torsion Preferences.

Dakota L. Folmsbee, David Ryan Koes, Geoffrey R. Hutchison

J. Chem. Inf. Model., December, 2023

Conformer Generation for Structure-Based Drug Design: How Many and How Good?

Andrew T. McNutt, Fatimah Bisiriyu, Sophia Song, Ananya Vyas, Geoffrey R. Hutchison, David Ryan Koes

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

Accelerating Inference in Molecular Diffusion Models with Latent Representations of Protein Structure.

Ian Dunn, David Ryan Koes

CoRR, 2023

2022

Improving <i>ΔΔG</i> Predictions with a Multitask Convolutional Siamese Network.

Andrew T. McNutt, David Ryan Koes

J. Chem. Inf. Model., 2022

2021

Correction to "SolTranNet - A Machine Learning Tool for Fast Aqueous Solubility Prediction".

Paul G. Francoeur, David Ryan Koes

J. Chem. Inf. Model., 2021

SolTranNet-A Machine Learning Tool for Fast Aqueous Solubility Prediction.

Paul G. Francoeur, David Ryan Koes

J. Chem. Inf. Model., 2021

GNINA 1.0: molecular docking with deep learning.

Andrew T. McNutt, Paul G. Francoeur, Rishal Aggarwal, Tomohide Masuda, Rocco Meli, Matthew Ragoza, Jocelyn Sunseri, David Ryan Koes

J. Cheminformatics, 2021

Generating 3D Molecules Conditional on Receptor Binding Sites with Deep Generative Models.

Matthew Ragoza, Tomohide Masuda, David Ryan Koes

CoRR, 2021

2020

libmolgrid: Graphics Processing Unit Accelerated Molecular Gridding for Deep Learning Applications.

Jocelyn Sunseri, David Ryan Koes

J. Chem. Inf. Model., 2020

Three-Dimensional Convolutional Neural Networks and a Cross-Docked Data Set for Structure-Based Drug Design.

Paul G. Francoeur, Tomohide Masuda, Jocelyn Sunseri, Andrew Jia, Richard B. Iovanisci, Ian Snyder, David Ryan Koes

J. Chem. Inf. Model., 2020

Generating 3D Molecular Structures Conditional on a Receptor Binding Site with Deep Generative Models.

Tomohide Masuda, Matthew Ragoza, David Ryan Koes

CoRR, 2020

Learning a Continuous Representation of 3D Molecular Structures with Deep Generative Models.

Matthew Ragoza, Tomohide Masuda, David Ryan Koes

CoRR, 2020

SidechainNet: An All-Atom Protein Structure Dataset for Machine Learning.

Jonathan E. King, David Ryan Koes

CoRR, 2020

2019

Convolutional neural network scoring and minimization in the D3R 2017 community challenge.

Jocelyn Sunseri, Jonathan E. King, Paul G. Francoeur, David Ryan Koes

J. Comput. Aided Mol. Des., 2019

libmolgrid: GPU Accelerated Molecular Gridding for Deep Learning Applications.

Jocelyn Sunseri, David Ryan Koes

CoRR, 2019

2018

The Pharmit backend: A computer systems approach to enabling interactive online drug discovery.

David Ryan Koes

IBM J. Res. Dev., 2018

Visualizing Convolutional Neural Network Protein-Ligand Scoring.

Joshua E. Hochuli, Alec Helbling, Tamar Skaist, Matthew Ragoza, David Ryan Koes

CoRR, 2018

2017

Protein-Ligand Scoring with Convolutional Neural Networks.

Matthew Ragoza, Joshua E. Hochuli, Elisa Idrobo, Jocelyn Sunseri, David Ryan Koes

J. Chem. Inf. Model., 2017

Ligand Pose Optimization with Atomic Grid-Based Convolutional Neural Networks.

Matthew Ragoza, Lillian Turner, David Ryan Koes

CoRR, 2017

2016

Pharmit: interactive exploration of chemical space.

Jocelyn Sunseri, David Ryan Koes

Nucleic Acids Res., 2016

A D3R prospective evaluation of machine learning for protein-ligand scoring.

Jocelyn Sunseri, Matthew Ragoza, Jasmine Collins, David Ryan Koes

J. Comput. Aided Mol. Des., 2016

2015

Indexing volumetric shapes with matching and packing.

David Ryan Koes, Carlos J. Camacho

Knowl. Inf. Syst., 2015

3Dmol.js: molecular visualization with WebGL.

Nicholas Rego, David Koes

Bioinform., 2015

2014

Shape-based virtual screening with volumetric aligned molecular shapes.

David Ryan Koes, Carlos J. Camacho

J. Comput. Chem., 2014

2013

Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise.

David Ryan Koes, Matthew P. Baumgartner, Carlos J. Camacho

J. Chem. Inf. Model., 2013

2012

ZINCPharmer: pharmacophore search of the ZINC database.

David Ryan Koes, Carlos J. Camacho

Nucleic Acids Res., 2012

PocketQuery: protein-protein interaction inhibitor starting points from protein-protein interaction structure.

David Ryan Koes, Carlos J. Camacho

Nucleic Acids Res., 2012

Small-molecule inhibitor starting points learned from protein-protein interaction inhibitor structure.

David Ryan Koes, Carlos J. Camacho

Bioinform., 2012

2011

Pharmer: Efficient and Exact Pharmacophore Search.

David Ryan Koes, Carlos J. Camacho

J. Chem. Inf. Model., 2011

2009

Register allocation deconstructed.

David Ryan Koes, Seth Copen Goldstein

Proceedings of the 12th International Workshop on Software and Compilers for Embedded Systems, 2009

2008

Near-optimal instruction selection on dags.

David Ryan Koes, Seth Copen Goldstein

Proceedings of the Sixth International Symposium on Code Generation and Optimization (CGO 2008), 2008

2006

A global progressive register allocator.

David Ryan Koes, Seth Copen Goldstein

Proceedings of the ACM SIGPLAN 2006 Conference on Programming Language Design and Implementation, 2006

2005

A Progressive Register Allocator for Irregular Architectures.

David Koes, Seth Copen Goldstein

Proceedings of the 3nd IEEE / ACM International Symposium on Code Generation and Optimization (CGO 2005), 2005

2004

Programmer specified pointer independence.

David Koes, Mihai Budiu, Girish Venkataramani

Proceedings of the 2004 workshop on Memory System Performance, 2004

2001

Precise Omnidirectional Camera Calibration.

Dennis Strelow, Jeffrey Mishler, David Koes, Sanjiv Singh

Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), 2001