Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis
Karren D. Yang, Samuel Goldman, Wengong Jin, Alex X. Lu, Regina Barzilay, Tommi S. Jaakkola, Caroline Uhler
2021Year
4Top-tier citations
Abstract
To evaluate our model, we propose a new set of metrics for biological image generation that are robust, interpretable, and relevant to practitioners. We show quantitatively that our method learns a meaningful embedding of the molecular intervention, which is translated into an image representation reflecting the biological effects of the intervention.
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Install the CLIlune papers fulltext 2217012b-1c3d-4db0-b7fc-cdccb934cbcdCited by top-tier papers4
- Removing Biases from Molecular Representations via Information MaximizationChenyu Wang, Sharut Gupta, Caroline Uhler, Tommi S. JaakkolaICLR 2024 · 11 citations
- TRIDENT: A Trimodal Cascade Generative Framework for Drug and RNA-Conditioned Cellular Morphology SynthesisRui Peng, Ziru Liu, Lingyuan Ye, Yuxing Lu et al.CVPR 2026 · 1 citation
- CellFlux: Simulating Cellular Morphology Changes via Flow MatchingYuhui Zhang, Yuchang Su, Chenyu Wang, Tianhong Li et al.ICML 2025
- MorphoDiff: Cellular Morphology Painting with Diffusion ModelsZeinab Navidi, Jun Ma, Esteban Miglietta, Le Liu et al.ICLR 2025
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