HippDB: a database of readily targeted helical protein-protein interactions. - Christina M. Bergey; Andrew M. Watkins; Paramjit S. Arora (Bioinform., 2013)

Accurate de novo design of hyperstable constrained peptides. - Gaurav Bhardwaj; Vikram Khipple Mulligan; Christopher D. Bahl; Jason M. Gilmore; Peta J. Harvey; Olivier Cheneval; Garry W. Buchko; Surya V. S. R. K. Pulavarti; Quentin Kaas; Alexander Eletsky; Po-Ssu Huang; William A. Johnsen; et al. (Nat., 2016)

Better together: Elements of successful scientific software development in a distributed collaborative community. - Julia Koehler Leman; Brian D. Weitzner; P. Douglas Renfrew; Steven M. Lewis; Rocco Moretti; Andrew M. Watkins; Vikram Khipple Mulligan; Sergey Lyskov; Jared Adolf-Bryfogle; Jason W. Labonte; Justyna Krys; RosettaCommons Consortium; et al. (PLoS Comput. Biol., 2020)

Predictive models of RNA degradation through dual crowdsourcing. - Hannah K. Wayment-Steele; Wipapat Kladwang; Andrew M. Watkins; Do Soon Kim; Bojan Tunguz; Walter Reade; Maggie Demkin; Jonathan Romano; Roger Wellington-Oguri; John J. Nicol; Jiayang Gao; Kazuki Onodera; et al. (CoRR, 2021)

Multi-segment preserving sampling for deep manifold sampler. - Daniel Berenberg; Jae Hyeon Lee; Simon Kelow; Ji Won Park; Andrew M. Watkins; Vladimir Gligorijevic; Richard Bonneau; Stephen Ra; Kyunghyun Cho (CoRR, 2022)

PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design. - Ji Won Park; Samuel Stanton; Saeed Saremi; Andrew M. Watkins; Henri Dwyer; Vladimir Gligorijevic; Richard Bonneau; Stephen Ra; Kyunghyun Cho (CoRR, 2022)

Deep learning models for predicting RNA degradation via dual crowdsourcing. - Hannah K. Wayment-Steele; Wipapat Kladwang; Andrew M. Watkins; Do Soon Kim; Bojan Tunguz; Walter Reade; Maggie Demkin; Jonathan Romano; Roger Wellington-Oguri; John J. Nicol; Jiayang Gao; Kazuki Onodera; et al. (Nat. Mac. Intell., 2022)

OpenProteinSet: Training data for structural biology at scale. - Gustaf Ahdritz; Nazim Bouatta; Sachin Kadyan; Lukas Jarosch; Daniel Berenberg; Ian Fisk; Andrew M. Watkins; Stephen Ra; Richard Bonneau; Mohammed AlQuraishi (NeurIPS, 2023)

3D molecule generation by denoising voxel grids. - Pedro O. Pinheiro; Joshua Rackers; Joseph Kleinhenz; Michael Maser; Omar Mahmood; Andrew M. Watkins; Stephen Ra; Vishnu Sresht; Saeed Saremi (NeurIPS, 2023)

SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers. - Michael Maser; Ji Won Park; Joshua Yao-Yu Lin; Jae Hyeon Lee; Nathan C. Frey; Andrew M. Watkins (CoRR, 2023)

MoleCLUEs: Optimizing Molecular Conformers by Minimization of Differentiable Uncertainty. - Michael Maser; Natasa Tagasovska; Jae Hyeon Lee; Andrew M. Watkins (CoRR, 2023)

Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms. - Samuel Stanton; Robert G. Alberstein; Nathan C. Frey; Andrew M. Watkins; Kyunghyun Cho (CoRR, 2024)

NEBULA: Neural Empirical Bayes Under Latent Representations for Efficient and Controllable Design of Molecular Libraries. - Ewa M. Nowara; Pedro O. Pinheiro; Sai Pooja Mahajan; Omar Mahmood; Andrew Martin Watkins; Saeed Saremi; Michael Maser (CoRR, 2024)

Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design. - Natasa Tagasovska; Ji Won Park; Matthieu Kirchmeyer; Nathan C. Frey; Andrew Martin Watkins; Aya Abdelsalam Ismail; Arian Rokkum Jamasb; Edith Lee; Tyler Bryson; Stephen Ra; Kyunghyun Cho (CoRR, 2024)

LLMs are Highly-Constrained Biophysical Sequence Optimizers. - Angelica Chen; Samuel Don Stanton; Robert G. Alberstein; Andrew M. Watkins; Richard Bonneau; Vladimir Gligorijevic; Kyunghyun Cho; Nathan C. Frey (CoRR, 2024)

Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteins. - Frédéric A. Dreyer; Jan Ludwiczak; Karolis Martinkus; Brennan Abanades; Robert G. Alberstein; Pan Kessel; Pranav Rao; Jae Hyeon Lee; Richard Bonneau; Andrew M. Watkins; Franziska Seeger (CoRR, 2025)

Do we need equivariant models for molecule generation? - Ewa M. Nowara; Joshua Rackers; Patricia Suriana; Pan Kessel; Max Shen 002; Andrew Martin Watkins; Michael Maser (CoRR, 2025)