Követés
Wengong Jin
Wengong Jin
Broad Institute of MIT and Harvard
E-mail megerősítve itt: csail.mit.edu - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
A deep learning approach to antibiotic discovery
JM Stokes, K Yang, K Swanson, W Jin, A Cubillos-Ruiz, NM Donghia, ...
Cell 180 (4), 688-702. e13, 2020
18052020
Junction Tree Variational Autoencoder for Molecular Graph Generation
W Jin, R Barzilay, T Jaakkola
International Conference on Machine Learning (ICML), 2018
15342018
Analyzing learned molecular representations for property prediction
K Yang, K Swanson, W Jin, C Coley, P Eiden, H Gao, A Guzman-Perez, ...
Journal of chemical information and modeling 59 (8), 3370-3388, 2019
13742019
A graph-convolutional neural network model for the prediction of chemical reactivity
CW Coley, W Jin, L Rogers, TF Jamison, TS Jaakkola, WH Green, ...
Chemical science 10 (2), 370-377, 2019
6492019
Predicting organic reaction outcomes with weisfeiler-lehman network
W Jin, C Coley, R Barzilay, T Jaakkola
Advances in neural information processing systems 30, 2017
3282017
Hierarchical Generation of Molecular Graphs using Structural Motifs
W Jin, R Barzilay, T Jaakkola
International Conference on Machine Learning (ICML), 2020
324*2020
Learning Multimodal Graph-to-Graph Translation for Molecular Optimization
W Jin, K Yang, R Barzilay, T Jaakkola
International Conference on Learning Representations (ICLR), 2018
2782018
Multi-Objective Molecule Generation using Interpretable Substructures
W Jin, R Barzilay, T Jaakkola
International Conference on Machine Learning (ICML), 2020
221*2020
Generative models for molecular discovery: Recent advances and challenges
C Bilodeau, W Jin, T Jaakkola, R Barzilay, KF Jensen
Wiley Interdisciplinary Reviews: Computational Molecular Science 12 (5), e1608, 2022
1792022
Deriving neural architectures from sequence and graph kernels
T Lei, W Jin, R Barzilay, T Jaakkola
International Conference on Machine Learning (ICML), 2017
1472017
Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii
G Liu, DB Catacutan, K Rathod, K Swanson, W Jin, JC Mohammed, ...
Nature Chemical Biology 19 (11), 1342-1350, 2023
1292023
Deep learning identifies synergistic drug combinations for treating COVID-19
W Jin, JM Stokes, RT Eastman, Z Itkin, AV Zakharov, JJ Collins, ...
Proceedings of the National Academy of Sciences 118 (39), e2105070118, 2021
1282021
Iterative refinement graph neural network for antibody sequence-structure co-design
W Jin, J Wohlwend, R Barzilay, T Jaakkola
International Conference on Learning Representations (ICLR), 2021
1102021
Antibody-Antigen Docking and Design via Hierarchical Equivariant Refinement
W Jin, R Barzilay, T Jaakkola
International Conference on Machine Learning (ICML), 2022
53*2022
Discovery of a structural class of antibiotics with explainable deep learning
F Wong, EJ Zheng, JA Valeri, NM Donghia, MN Anahtar, S Omori, A Li, ...
Nature 626 (7997), 177-185, 2024
482024
Enforcing Predictive Invariance across Structured Biomedical Domains
W Jin, R Barzilay, T Jaakkola
arXiv preprint arXiv:2006.03908, 2020
40*2020
Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back
BA Koscher, RB Canty, MA McDonald, KP Greenman, CJ McGill, ...
Science 382 (6677), eadi1407, 2023
262023
Functional Transparency for Structured Data: a Game-Theoretic Approach
GH Lee, W Jin, D Alvarez-Melis, TS Jaakkola
International Conference on Machine Learning (ICML), 2019
232019
Improving Molecular Design by Stochastic Iterative Target Augmentation
K Yang, W Jin, K Swanson, R Barzilay, T Jaakkola
International Conference on Machine Learning (ICML), 2020
222020
Mol2Image: improved conditional flow models for molecule to image synthesis
K Yang, S Goldman, W Jin, AX Lu, R Barzilay, T Jaakkola, C Uhler
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
16*2021
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