activity
20172023
most citedPredicting Organic Reaction Outcomes with Weisfeiler-Lehman Network

191 citations · 444 across the 9 of their papers we have counts for

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Showing q-bio.BMShow all

5 papers · 1 filter

q-bio.BM2023★ 4 cited

Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation

Wengong Jin, Siranush Sarkizova, Xun Chen +2

Protein-ligand binding prediction is a fundamental problem in AI-driven drug discovery. Prior work focused on supervised learning methods using a large set of binding affinity data…

q-bio.BM2022★ 12 cited

Antibody-Antigen Docking and Design via Hierarchical Equivariant Refinement

Wengong Jin, Regina Barzilay, Tommi Jaakkola

Computational antibody design seeks to automatically create an antibody that binds to an antigen. The binding affinity is governed by the 3D binding interface where antibody residu…

q-bio.BM2021★ 66 cited

Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design

Wengong Jin, Jeremy Wohlwend, Regina Barzilay +1

Antibodies are versatile proteins that bind to pathogens like viruses and stimulate the adaptive immune system. The specificity of antibody binding is determined by complementarity…

q-bio.BM2020★ 3 cited

Discovering Synergistic Drug Combinations for COVID with Biological Bottleneck Models

Wengong Jin, Regina Barzilay, Tommi Jaakkola

Drug combinations play an important role in therapeutics due to its better efficacy and reduced toxicity. Recent approaches have applied machine learning to identify synergistic co…

q-bio.BM2020★ 6 cited

Improved Conditional Flow Models for Molecule to Image Synthesis

Karren Yang, Samuel Goldman, Wengong Jin +4

In this paper, we aim to synthesize cell microscopy images under different molecular interventions, motivated by practical applications to drug development. Building on the recent…