mlsanityData to 7 Oct 2026

Sifting through the Noise: A Survey of Diffusion Probabilistic Models and Their Applications to Biomolecules

arXiv 2406.01622 ↗First posted 31 May 2024q-bio.BM cs.AI cs.LGcited by 1

On the map: Diffusion models → Flow matching, time series and science

Abstract (arXiv)

Diffusion probabilistic models have made their way into a number of high-profile applications since their inception. In particular, there has been a wave of research into using diffusion models in the prediction and design of biomolecular structures and sequences. Their growing ubiquity makes it imperative for researchers in these fields to understand them. This paper serves as a general overview for the theory behind these models and the current state of research. We first introduce diffusion models and discuss common motifs used when applying them to biomolecules. We then present the significant outcomes achieved through the application of these models in generative and predictive tasks. This survey aims to provide readers with a comprehensive understanding of the increasingly critical role of diffusion models.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Flow matching, time series and science, one of 14 directions in Diffusion models. Builds on 61 of its 145 references that are in the map. First posted on arXiv 31 May 2024.

Builds on

61 of 145 references.

Closest ancestors · 20

Same direction, newest first

  1. 2024AlphaFold Meets Flow Matching for Generating Protein Ensembles7 Feb
  2. 2023Latent Diffusion Model for DNA Sequence Generation9 Oct
  3. 2023SE(3)-Stochastic Flow Matching for Protein Backbone Generation3 Oct
  4. 2023Backdiff: a diffusion model for generalized transferable protein backmapping3 Oct
  5. 2023Score dynamics: scaling molecular dynamics with picoseconds timestep via conditional diffusion model2 Oct
  6. 2023Bayesian Flow Networks14 Aug
  7. 2023DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein Traces23 Jul
  8. 2023Graph Denoising Diffusion for Inverse Protein Folding29 Jun
  9. 2023DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing1 Jun
  10. 2023A Latent Diffusion Model for Protein Structure Generation6 May
  11. 2023DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models8 Apr
  12. 2023EigenFold: Generative Protein Structure Prediction with Diffusion Models5 Apr
8 more
  1. 2023SE(3) diffusion model with application to protein backbone generation5 Feb
  2. 2023Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics1 Feb
  3. 2022Flow Matching for Generative Modeling6 Oct
  4. 2022Protein structure generation via folding diffusion30 Sep
  5. 2022Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem8 Jun
  6. 2022DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations19 Apr
  7. 2022Flow-matching -- efficient coarse-graining of molecular dynamics without forces21 Mar
  8. 2022GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation6 Mar

Other references · 41

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  6. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  7. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  8. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  9. 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 2,994
  10. 2021Structured Denoising Diffusion Models in Discrete State-Spacescited by 1,665
  11. 2018Glow: Generative Flow with Invertible 1x1 Convolutionscited by 1,539
  12. 2022Diffusion Models in Vision: A Surveycited by 1,008
29 more
  1. 2021E(n) Equivariant Graph Neural Networkscited by 951
  2. 2018Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point cloudscited by 735
  3. 2020SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networkscited by 602
  4. 2021Argmax Flows and Multinomial Diffusion: Learning Categorical Distributionscited by 566
  5. 2019Sliced Score Matching: A Scalable Approach to Density and Score Estimationcited by 381
  6. 2020Learning from Protein Structure with Geometric Vector Perceptronscited by 308
  7. 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 307
  8. 2022Torsional Diffusion for Molecular Conformer Generationcited by 262
  9. 2020Deep Network Approximation for Smooth Functionscited by 163
  10. 2021Learning Gradient Fields for Molecular Conformation Generationcited by 162
  11. 2023Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Modelscited by 155
  12. 2021DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanismcited by 154
  13. 2022EquiBind: Geometric Deep Learning for Drug Binding Structure Predictioncited by 143
  14. 2022SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusioncited by 125
  15. 2022Riemannian Diffusion Modelscited by 120
  16. 2022DALL-E-Bot: Introducing Web-Scale Diffusion Models to Roboticscited by 105
  17. 2021Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Schemecited by 99
  18. 2022PiFold: Toward effective and efficient protein inverse foldingcited by 82
  19. 2023Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Cloudscited by 53
  20. 2022AlphaDesign: A graph protein design method and benchmark on AlphaFoldDBcited by 39
  21. 2022State-specific protein-ligand complex structure prediction with a multi-scale deep generative modelcited by 35
  22. 2023Str2Str: A Score-based Framework for Zero-shot Protein Conformation Samplingcited by 29
  23. 2024Deep Confident Steps to New Pockets: Strategies for Docking Generalizationcited by 27
  24. 2015Protein secondary structure prediction using deep convolutional neural fieldscited by 12
  25. 2023Do Deep Learning Models Really Outperform Traditional Approaches in Molecular Docking?cited by 11
  26. 2023Towards Joint Sequence-Structure Generation of Nucleic Acid and Protein Complexes with SE(3)-Discrete Diffusioncited by 9
  27. 2021ItoTTS and ItoWave: Linear Stochastic Differential Equation Is All You Need For Audio Generationcited by 6
  28. 2022Denoising Diffusion Probabilistic Models for Styled Walking Synthesiscited by 6
  29. 2023ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a protein language diffusion modelcited by 5

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Citing papers per year: 2025: 1.

1 paper.

  1. 2025From thermodynamics to protein design: Diffusion models for biomolecule generation towards autonomous protein engineeringcited by 2

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