Quantifying the Relationships among Drug Classes. - Jérôme Hert; Michael J. Keiser; John J. Irwin; Tudor I. Oprea; Brian K. Shoichet (J. Chem. Inf. Model., 2008)

A Mapping of Drug Space from the Viewpoint of Small Molecule Metabolism. - James Corey Adams; Michael J. Keiser; Li Basuino; Henry F. Chambers; Deok-Sun Lee; Olaf G. Wiest; Patricia C. Babbitt (PLoS Comput. Biol., 2009)

Predicted Biological Activity of Purchasable Chemical Space. - John J. Irwin; Garrett Gaskins; Teague Sterling; Michael M. Mysinger; Michael J. Keiser (J. Chem. Inf. Model., 2018)

Global Saliency: Aggregating Saliency Maps to Assess Dataset Artefact Bias. - Jacob Pfau; Albert T. Young; Maria L. Wei; Michael J. Keiser (CoRR, 2019)

Attention-Based Learning on Molecular Ensembles. - Kangway V. Chuang; Michael J. Keiser (CoRR, 2020)

Adding Stochastic Negative Examples into Machine Learning Improves Molecular Bioactivity Prediction. - Elena L. Cáceres; Nicholas C. Mew; Michael J. Keiser (J. Chem. Inf. Model., 2020)

Robust Semantic Interpretability: Revisiting Concept Activation Vectors. - Jacob Pfau; Albert T. Young; Jerome Wei; Maria L. Wei; Michael J. Keiser (CoRR, 2021)

Stress testing reveals gaps in clinic readiness of image-based diagnostic artificial intelligence models. - Albert T. Young; Kristen Fernandez; Jacob Pfau; Rasika Reddy; Nhat Anh Cao; Max Y. von Franque; Arjun Johal; Benjamin V. Wu; Rachel R. Wu; Jennifer Y. Chen; Raj P. Fadadu; Juan A. Vasquez; et al. (npj Digit. Medicine, 2021)

A Biomedical Open Knowledge Network Harnesses the Power of AI to Understand Deep Human Biology. - Sergio E. Baranzini; Katy Börner; John H. Morris; Charlotte A. Nelson; Karthik Soman; Erica Schleimer; Michael J. Keiser; Mark A. Musen; Roger Pearce; Tahsin Reza; Brett Smith; Bruce William Herr II; et al. (AI Mag., 2022)

A single-cell gene expression language model. - William Connell; Umair Khan; Michael J. Keiser (CoRR, 2022)

Learning Melanocytic Cell Masks from Adjacent Stained Tissue. - Mikio Tada; Maria L. Wei; Michael J. Keiser (CoRR, 2022)

Prioritizing Virtual Screening with Interpretable Interaction Fingerprints. - Alexandre V. Fassio; Laura Shub; Luca Ponzoni; Jessica McKinley; Matthew J. O'Meara; Rafaela Salgado Ferreira; Michael J. Keiser; Raquel Cardoso de Melo Minardi (J. Chem. Inf. Model., 2022)

Trans-channel fluorescence learning improves high-content screening for Alzheimer's disease therapeutics. - Daniel R. Wong; Jay Conrad; Noah R. Johnson; Jacob Ayers; Annelies Laeremans; Joanne C. Lee; Jisoo Lee; Stanley B. Prusiner; Sourav Bandyopadhyay; Atul J. Butte; Nick A. Paras; Michael J. Keiser (Nat. Mach. Intell., 2022)

The scalable precision medicine open knowledge engine (SPOKE): a massive knowledge graph of biomedical information. - John H. Morris; Karthik Soman; Rabia E. Akbas; Xiaoyuan Zhou; Brett Smith; Elaine C. Meng; Conrad C. Huang; Gabriel Cerono; Gundolf Schenk; Angela Rizk-Jackson; Adil Harroud; Lauren M. Sanders; et al. (Bioinform., 2023)

Autoregressive fragment-based diffusion for pocket-aware ligand design. - Mahdi Ghorbani; Leo Gendelev; Paul Beroza; Michael J. Keiser (CoRR, 2024)

Proximity Graph Networks: Predicting Ligand Affinity with Message Passing Neural Networks. - Zachary J. Gale-Day; Laura Shub; Kangway V. Chuang; Michael J. Keiser (J. Chem. Inf. Model., 2024)

Retrieval Augmented Docking Using Hierarchical Navigable Small Worlds. - Brendan W. Hall; Michael J. Keiser (J. Chem. Inf. Model., 2024)

Fuzz Testing Molecular Representation Using Deep Variational Anomaly Generation. - Victor H. R. Nogueira; Rishabh Sharma; Rafael V. C. Guido; Michael J. Keiser (J. Chem. Inf. Model., 2025)

ChromaFactor: Deconvolution of single-molecule chromatin organization with non-negative matrix factorization. - Laura M. Gunsalus; Michael J. Keiser; Katherine S. Pollard (PLoS Comput. Biol., 2025)