publications

2024

1. Discovery of a structural class of antibiotics with explainable deep learning

   Felix Wong, Erica J Zheng, Jacqueline A Valeri, and 8 more authors

   Nature, 2024
2. AI-driven discovery of synergistic drug combinations against pancreatic cancer

   Mohsen Pourmousa, Sankalp Jain, Elena Barnaeva, and 8 more authors

   BioRxiv, 2024
3. RNAFlow: RNA Structure & Sequence Design via Inverse Folding-Based Flow Matching

   Divya Nori, and Wengong Jin

   In International Conference on Machine Learning (ICML), 2024
4. SurfPro: Functional Protein Design Based on Continuous Surface

   Zhenqiao Song, Tinglin Huang, Lei Li, and 1 more author

   In International Conference on Machine Learning (ICML), 2024
5. Generative Enzyme Design Guided by Functionally Important Sites and Small-Molecule Substrates

   Zhenqiao Song, Yunlong Zhao, Wenxian Shi, and 3 more authors

   In International Conference on Machine Learning (ICML), 2024
6. Protein-Nucleic Acid Complex Modeling with Frame Averaging Transformer

   Tinglin Huang, Zhenqiao Song, Rex Ying, and 1 more author

   arXiv preprint arXiv:2406.09586, 2024

2023

1. Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler’s Rotation Equation

   Wengong Jin, Siranush Sarkizova, Xun Chen, and 2 more authors

   In Neural Information Processing Systems (NeurIPS), 2023
2. Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back

   Brent A Koscher, Richard B Canty, Matthew A McDonald, and 8 more authors

   Science, 2023
3. Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii

   Gary Liu, Denise B Catacutan, Khushi Rathod, and 8 more authors

   Nature Chemical Biology, 2023
4. DSMBind: SE (3) denoising score matching for unsupervised binding energy prediction and nanobody design

   Wengong Jin, Xun Chen, Amrita Vetticaden, and 4 more authors

   bioRxiv, 2023

2022

1. Generating molecules with optimized aqueous solubility using iterative graph translation

   Camille Bilodeau, Wengong Jin, Hongyun Xu, and 6 more authors

   Reaction Chemistry & Engineering, 2022
2. Generative models for molecular discovery: Recent advances and challenges

   Camille Bilodeau, Wengong Jin, Tommi Jaakkola, and 2 more authors

   Wiley Interdisciplinary Reviews: Computational Molecular Science, 2022
3. Antibody-Antigen Docking and Design via Hierarchical Equivariant Refinement

   Wengong Jin, Regina Barzilay, and Tommi Jaakkola

   In International Conference on Machine Learning (ICML), 2022

2021

1. Mol2Image: improved conditional flow models for molecule to image synthesis

   Karren Yang, Samuel Goldman, Wengong Jin, and 4 more authors

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021
2. Deep learning identifies synergistic drug combinations for treating COVID-19

   Wengong Jin, Jonathan M Stokes, Richard T Eastman, and 5 more authors

   Proceedings of the National Academy of Sciences, 2021
3. Iterative refinement graph neural network for antibody sequence-structure co-design

   Wengong Jin, Jeremy Wohlwend, Regina Barzilay, and 1 more author

   In International Conference on Learning Representations (ICLR), 2021

2020

1. Hierarchical Generation of Molecular Graphs using Structural Motifs

   Wengong Jin, Regina Barzilay, and Tommi Jaakkola

   In International Conference on Machine Learning (ICML), 2020
2. Multi-Objective Molecule Generation using Interpretable Substructures

   Wengong Jin, Regina Barzilay, and Tommi Jaakkola

   In International Conference on Machine Learning (ICML), 2020
3. Improving Molecular Design by Stochastic Iterative Target Augmentation

   Kevin Yang, Wengong Jin, Kyle Swanson, and 2 more authors

   In International Conference on Machine Learning (ICML), 2020
4. A deep learning approach to antibiotic discovery

   Jonathan M Stokes, Kevin Yang, Kyle Swanson, and 8 more authors

   Cell, 2020
5. Enforcing Predictive Invariance across Structured Biomedical Domains

   Wengong Jin, Regina Barzilay, and Tommi Jaakkola

   arXiv preprint arXiv:2006.03908, 2020

2019

1. Functional Transparency for Structured Data: a Game-Theoretic Approach

   Guang-He Lee, Wengong Jin, David Alvarez-Melis, and 1 more author

   In International Conference on Machine Learning (ICML), 2019
2. Analyzing learned molecular representations for property prediction

   Kevin Yang, Kyle Swanson, Wengong Jin, and 8 more authors

   Journal of chemical information and modeling, 2019
3. A graph-convolutional neural network model for the prediction of chemical reactivity

   Connor W Coley, Wengong Jin, Luke Rogers, and 5 more authors

   Chemical science, 2019

2018

1. Junction Tree Variational Autoencoder for Molecular Graph Generation

   Wengong Jin, Regina Barzilay, and Tommi Jaakkola

   In International Conference on Machine Learning (ICML), 2018
2. Learning Multimodal Graph-to-Graph Translation for Molecular Optimization

   Wengong Jin, Kevin Yang, Regina Barzilay, and 1 more author

   In International Conference on Learning Representations (ICLR), 2018

2017

1. Deriving neural architectures from sequence and graph kernels

   Tao Lei, Wengong Jin, Regina Barzilay, and 1 more author

   In International Conference on Machine Learning (ICML), 2017
2. Predicting organic reaction outcomes with weisfeiler-lehman network

   Wengong Jin, Connor Coley, Regina Barzilay, and 1 more author

   Advances in neural information processing systems, 2017