mlsanityData to 7 Oct 2026

Solving Inverse Problems in Protein Space Using Diffusion-Based Priors

arXiv 2406.04239 ↗First posted 6 Jun 2024cs.LGcited by 13

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Abstract (arXiv)

The interaction of a protein with its environment can be understood and controlled via its 3D structure. Experimental methods for protein structure determination, such as X-ray crystallography or cryogenic electron microscopy, shed light on biological processes but introduce challenging inverse problems. Learning-based approaches have emerged as accurate and efficient methods to solve these inverse problems for 3D structure determination, but are specialized for a predefined type of measurement. Here, we introduce a versatile framework to turn biophysical measurements, such as cryo-EM density maps, into 3D atomic models. Our method combines a physics-based forward model of the measurement process with a pretrained generative model providing a task-agnostic, data-driven prior. Our method outperforms posterior sampling baselines on linear and non-linear inverse problems. In particular, it is the first diffusion-based method for refining atomic models from cryo-EM maps and building atomic models from sparse distance matrices.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 28 of its 95 references that are in the map. First posted on arXiv 6 Jun 2024.

Builds on

28 of 95 references.

References · 28

  1. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
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16 more
  1. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Modelscited by 514
  2. 2022Improving Diffusion Models for Inverse Problems using Manifold Constraintscited by 501
  3. 2021SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Modelscited by 415
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  7. 2021Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contractioncited by 306
  8. 2021Robust Compressed Sensing MRI with Deep Generative Priorscited by 284
  9. 2022Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problemcited by 229
  10. 2022Riemannian Score-Based Generative Modellingcited by 216
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  12. 2023State of the Art on Diffusion Models for Visual Computingcited by 126
  13. 2022Protein structure generation via folding diffusioncited by 113
  14. 2022Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Modelscited by 97
  15. 2023EigenFold: Generative Protein Structure Prediction with Diffusion Modelscited by 63
  16. 2023Provable Probabilistic Imaging using Score-Based Generative Priorscited by 51

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 9; 2026: 2.

13 papers.

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  1. 2025Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approachcited by 18
  2. 2025Solving Linear-Gaussian Bayesian Inverse Problems with Decoupled Diffusion Sequential Monte Carlocited by 9
  3. 2025Multiscale guidance of protein structure prediction with heterogeneous cryo-EM datacited by 8
  4. 2025Unlocking hidden biomolecular conformational landscapes in diffusion models at inference timecited by 7
  5. 2025ESS-Flow: Training-free guidance of flow-based models as inference in source spacecited by 6
  6. 2024Stiefel Flow Matching for Moment-Constrained Structure Elucidationcited by 5
  7. 2024CryoFM: A Flow-based Foundation Model for Cryo-EM Densitiescited by 4
  8. 2025Dual Ascent Diffusion for Inverse Problemscited by 3
  9. 2025Representing local protein environments with machine learning force fieldscited by 2
  10. 2025Adaptive Multimodal Protein Plug-and-Play with Diffusion-Based Priorscited by 1
  11. 2025Valid Property-Enhanced Contrastive Learning for Targeted Optimization & Resampling for Novel Drug Designcited by 0
  12. 2026CrystalBoltz: End-to-End Protein Structure Determination via Experiment-Guided Diffusion for X-Ray Crystallographycited by 0
1 more
  1. 2026A Mean-Field Framework for Inference-Time Distributional Control of Diffusion Modelscited by 0