David Ryan Koes

46 papers A* 1A 1C 1Journal 43

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	BoltzNCE: Learning Likelihoods for Boltzmann Generation with Stochastic Interpolants and Noise Contrastive Estimation. CoRR Rishal Aggarwal, Jacky Chen, Nicholas M. Boffi, David Ryan Koes
2025	J	`jnl`	FlowMol3: Flow Matching for 3D De Novo Small-Molecule Generation. CoRR Ian Dunn, David Ryan Koes
2025	J	`jnl`	GEOM-Drugs Revisited: Toward More Chemically Accurate Benchmarks for 3D Molecule Generation. CoRR Filipp Nikitin, Ian Dunn, David Ryan Koes, Olexandr Isayev
2025	J	`jnl`	GNINA 1.3: the next increment in molecular docking with deep learning. J. Cheminformatics Andrew T. McNutt, Yanjing Li, Rocco Meli, Rishal Aggarwal, David Ryan Koes
2025	J	`jnl`	OMTRA: A Multi-Task Generative Model for Structure-Based Drug Design. CoRR Ian Dunn, Liv Toft, Tyler Katz, Juhi Gupta, Riya Shah, Ramith Hettiarachchi, David Ryan Koes
2025	J	`jnl`	PharmacoForge: pharmacophore generation with diffusion models. Frontiers Bioinform. Emma L. Flynn, Riya Shah, Ian Dunn, Rishal Aggarwal, David Ryan Koes
2024	J	`jnl`	BigBind: Learning from Nonstructural Data for Structure-Based Virtual Screening. J. Chem. Inf. Model. Michael Brocidiacono, Paul G. Francoeur, Rishal Aggarwal, Konstantin I. Popov, David Ryan Koes, Alexander Tropsha
2024	J	`jnl`	CACHE Challenge #1: Docking with GNINA Is All You Need. J. Chem. Inf. Model. Ian Dunn, Somayeh Pirhadi, Yao Wang, Smmrithi Ravindran, Carter Concepcion, David Ryan Koes
2024	J	`jnl`	CENsible: Interpretable Insights into Small-Molecule Binding with Context Explanation Networks. J. Chem. Inf. Model. Roshni Bhatt, David Ryan Koes, Jacob D. Durrant
2024	J	`jnl`	Exploring Discrete Flow Matching for 3D De Novo Molecule Generation. CoRR Ian Dunn, David Ryan Koes
2024	J	`jnl`	Mixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generation. CoRR Ian Dunn, David Ryan Koes
2024	J	`jnl`	Open-ComBind: harnessing unlabeled data for improved binding pose prediction. J. Comput. Aided Mol. Des. Andrew T. McNutt, David Ryan Koes
2024	J	`jnl`	SPRINT Enables Interpretable and Ultra-Fast Virtual Screening against Thousands of Proteomes. CoRR Andrew T. McNutt, Abhinav Adduri, Caleb N. Ellington, Monica T. Dayao, Eric P. Xing, Hosein Mohimani, David Ryan Koes
2023	J	`jnl`	Accelerating Inference in Molecular Diffusion Models with Latent Representations of Protein Structure. CoRR Ian Dunn, David Ryan Koes
2023	J	`jnl`	Conformer Generation for Structure-Based Drug Design: How Many and How Good? J. Chem. Inf. Model. Andrew T. McNutt, Fatimah Bisiriyu, Sophia Song, Ananya Vyas, Geoffrey R. Hutchison, David Ryan Koes
2023	J	`jnl`	Systematic Comparison of Experimental Crystallographic Geometries and Gas-Phase Computed Conformers for Torsion Preferences. J. Chem. Inf. Model. Dakota L. Folmsbee, David Ryan Koes, Geoffrey R. Hutchison
2022	J	`jnl`	Improving J. Chem. Inf. Model. Andrew T. McNutt, David Ryan Koes
2021	J	`jnl`	Correction to "SolTranNet - A Machine Learning Tool for Fast Aqueous Solubility Prediction". J. Chem. Inf. Model. Paul G. Francoeur, David Ryan Koes
2021	J	`jnl`	GNINA 1.0: molecular docking with deep learning. J. Cheminformatics Andrew T. McNutt, Paul G. Francoeur, Rishal Aggarwal, Tomohide Masuda, Rocco Meli, Matthew Ragoza, Jocelyn Sunseri, David Ryan Koes
2021	J	`jnl`	Generating 3D Molecules Conditional on Receptor Binding Sites with Deep Generative Models. CoRR Matthew Ragoza, Tomohide Masuda, David Ryan Koes
2021	J	`jnl`	SolTranNet-A Machine Learning Tool for Fast Aqueous Solubility Prediction. J. Chem. Inf. Model. Paul G. Francoeur, David Ryan Koes
2020	J	`jnl`	Generating 3D Molecular Structures Conditional on a Receptor Binding Site with Deep Generative Models. CoRR Tomohide Masuda, Matthew Ragoza, David Ryan Koes
2020	J	`jnl`	Learning a Continuous Representation of 3D Molecular Structures with Deep Generative Models. CoRR Matthew Ragoza, Tomohide Masuda, David Ryan Koes
2020	J	`jnl`	SidechainNet: An All-Atom Protein Structure Dataset for Machine Learning. CoRR Jonathan E. King, David Ryan Koes
2020	J	`jnl`	Three-Dimensional Convolutional Neural Networks and a Cross-Docked Data Set for Structure-Based Drug Design. J. Chem. Inf. Model. Paul G. Francoeur, Tomohide Masuda, Jocelyn Sunseri, Andrew Jia, Richard B. Iovanisci, Ian Snyder, David Ryan Koes
2020	J	`jnl`	libmolgrid: Graphics Processing Unit Accelerated Molecular Gridding for Deep Learning Applications. J. Chem. Inf. Model. Jocelyn Sunseri, David Ryan Koes
2019	J	`jnl`	Convolutional neural network scoring and minimization in the D3R 2017 community challenge. J. Comput. Aided Mol. Des. Jocelyn Sunseri, Jonathan E. King, Paul G. Francoeur, David Ryan Koes
2019	J	`jnl`	libmolgrid: GPU Accelerated Molecular Gridding for Deep Learning Applications. CoRR Jocelyn Sunseri, David Ryan Koes
2018	J	`jnl`	The Pharmit backend: A computer systems approach to enabling interactive online drug discovery. IBM J. Res. Dev. David Ryan Koes
2018	J	`jnl`	Visualizing Convolutional Neural Network Protein-Ligand Scoring. CoRR Joshua E. Hochuli, Alec Helbling, Tamar Skaist, Matthew Ragoza, David Ryan Koes
2017	J	`jnl`	Ligand Pose Optimization with Atomic Grid-Based Convolutional Neural Networks. CoRR Matthew Ragoza, Lillian Turner, David Ryan Koes
2017	J	`jnl`	Protein-Ligand Scoring with Convolutional Neural Networks. J. Chem. Inf. Model. Matthew Ragoza, Joshua E. Hochuli, Elisa Idrobo, Jocelyn Sunseri, David Ryan Koes
2016	J	`jnl`	A D3R prospective evaluation of machine learning for protein-ligand scoring. J. Comput. Aided Mol. Des. Jocelyn Sunseri, Matthew Ragoza, Jasmine Collins, David Ryan Koes
2016	J	`jnl`	Pharmit: interactive exploration of chemical space. Nucleic Acids Res. Jocelyn Sunseri, David Ryan Koes
2016	J	`jnl`	Protein-Ligand Scoring with Convolutional Neural Networks. CoRR Matthew Ragoza, Joshua E. Hochuli, Elisa Idrobo, Jocelyn Sunseri, David Ryan Koes
2015	J	`jnl`	Indexing volumetric shapes with matching and packing. Knowl. Inf. Syst. David Ryan Koes, Carlos J. Camacho
2014	J	`jnl`	Shape-based virtual screening with volumetric aligned molecular shapes. J. Comput. Chem. David Ryan Koes, Carlos J. Camacho
2013	J	`jnl`	Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise. J. Chem. Inf. Model. David Ryan Koes, Matthew P. Baumgartner, Carlos J. Camacho
2012	J	`jnl`	PocketQuery: protein-protein interaction inhibitor starting points from protein-protein interaction structure. Nucleic Acids Res. David Ryan Koes, Carlos J. Camacho
2012	J	`jnl`	Small-molecule inhibitor starting points learned from protein-protein interaction inhibitor structure. Bioinform. David Ryan Koes, Carlos J. Camacho
2012	J	`jnl`	Small-molecule inhibitor starting points learned from protein-protein interaction inhibitor structure. Bioinform. David Ryan Koes, Carlos J. Camacho
2012	J	`jnl`	ZINCPharmer: pharmacophore search of the ZINC database. Nucleic Acids Res. David Ryan Koes, Carlos J. Camacho
2011	J	`jnl`	Pharmer: Efficient and Exact Pharmacophore Search. J. Chem. Inf. Model. David Ryan Koes, Carlos J. Camacho
2009	C	`conf`	Register allocation deconstructed. SCOPES David Ryan Koes, Seth Copen Goldstein
2008	A	`conf`	Near-optimal instruction selection on dags. CGO David Ryan Koes, Seth Copen Goldstein
2006	A*	`conf`	A global progressive register allocator. PLDI David Ryan Koes, Seth Copen Goldstein