Awesome-Flow-Matching-Biology

A curated collection of papers, tools, and resources accompanying Flow Matching Meets Biology and Life Science: A Survey (arXiv 2025).

Flow matching is an emerging framework for generative modeling. This repository tracks its applications across biology and life sciences.

✨ This repository is continuously updated — star ⭐ it to stay up to date!

📖 If you find these resources helpful, please consider citing our survey (see Citations).

Why Flow Matching for Biology?

Flow Matching (FM) has recently emerged as a powerful paradigm for generative modeling, offering a flexible and scalable framework applicable across a wide range of biological domains. By constructing continuous probability trajectories between simple and complex distributions, FM provides an efficient and principled method to model high-dimensional, structured biological data while preserving structural and geometric constraints.

Contributing

Contributions are welcome! If you spot errors or know of relevant papers/tools, please open an issue or submit a pull request.

Badge tip: Use shields.io for consistent paper/code badges. Example: ![Paper](https://img.shields.io/badge/Paper-arXiv-b31b1b?style=flat-square). We've created templates for different publishers:

• arXiv: [![Paper](https://img.shields.io/badge/Paper-arXiv-b31b1b?style=flat-square&logo=arxiv&logoColor=white)]
• OpenReview: [![Paper](https://img.shields.io/badge/Paper-OpenReview-0f9973?style=flat-square)]
• Nature: [![Paper](https://img.shields.io/badge/Paper-Nature-4e9a06?style=flat-square)]
• NeurIPS: [![Paper](https://img.shields.io/badge/Paper-NeurIPS-8a2be2?style=flat-square)]

Overview

Contents

• Awesome-Flow-Matching-Biology
  • Why Flow Matching for Biology?
  • Contributing
  • Overview
  • Contents
  • Flow Matching Basics
    • General FM
      • Conditional FM
      • Rectified FM
      • Non-Euclidean FM
    • Discrete FM
      • CTMC
      • Simplex
  • Bio Sequence Modeling
    • DNA Sequence
    • RNA Sequence
    • Whole-Genome
    • Antibody Sequence
  • Molecule Generation and Design
    • 2D Molecule Generation
    • 3D Molecule Generation
      • SE(3)-equivariant
      • Efficiency
      • Guided Generation
    • Conditional Molecule Design and Applications
  • Protein Generation
    • Unconditional Generation
      • Backbone Generation
      • Co-design Generation
    • Conditional Generation
      • Motif-scaffolding
      • Pocket & Binder Design
    • Structure Prediction
      • Conformer Prediction
      • Side-chain Packing
      • Docking Prediction
    • Peptide and Antibody Generation
  • Other Biology Applications
    • Dynamic Cell Trajectory
    • Bio-Image Generation
    • Spatial Transcriptomics
    • Neural Activities
  • Datasets and Software Tools
  • Citations

Flow Matching Basics

General FM

Conditional FM

1. Building normalizing flows with stochastic interpolants ICLR 2023

   Michael S. Albergo, Eric Vanden-Eijnden , 2023

2. Variational flow matching for graph generation NeurIPS 2024

   Floor Eijkelboom, Grigory Bartosh, Christian Andersson Naesseth, Max Welling, Jan-Willem van de Meent , 2024

3. Flow matching for generative modeling ICLR 2023

   Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, Matt Le , 2023

4. Improving and generalizing flow-based generative models with minibatch optimal transport TMLR

   Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio , 2024

Rectified FM

1. Optimal flow matching: Learning straight trajectories in just one step NeurIPS 2024

   Nikita Kornilov, Petr Mokrov, Alexander Gasnikov, Alexander Korotin , 2024

2. Improving and generalizing flow-based generative models with minibatch optimal transport TMLR

   Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio , 2023

3. Improving the training of rectified flows NeurIPS 2024

   Sangyun Lee, Zinan Lin, Giulia Fanti , 2024

4. Flow straight and fast: Learning to generate and transfer data with rectified flow ICLR 2023

   Xingchao Liu, Chengyue Gong, Qiang Liu , 2023

Non-Euclidean FM

1. Flow matching on general geometries ICLR 2024

   Ricky T. Q. Chen, Yaron Lipman , 2023

2. α-flow: A unified framework for continuous-state discrete flow matching models preprint

   Cheng Cheng, Jiahao Li, Jianfei Fan, Ge Liu , 2025

3. Fisher flow matching for generative modeling over discrete data NeurIPS 2024

   Oscar Davis, Samuel Kessler, Mircea Petrache, Ismail Ceylan, Michael Bronstein, Joey Bose , 2024

4. Neural manifold ordinary differential equations NeurIPS 2020

   Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser Nam Lim, Christopher M. De Sa , 2020

5. Riemannian continuous normalizing flows NeurIPS 2020

   Emile Mathieu, Maximilian Nickel , 2020

Discrete FM

CTMC

1. Discrete flow matching NeurIPS 2024

   Itai Gat, Tal Remez, Neta Shaul, Felix Kreuk, Ricky T. Q. Chen, Gabriel Synnaeve, Yossi Adi, Yaron Lipman , 2024

2. α-flow: A unified framework for continuous-state discrete flow matching models arXiv

   Cheng Cheng, Jiahao Li, Jianfei Fan, Ge Liu , 2025

3. Fisher flow matching for generative modeling over discrete data NeurIPS 2024

   Oscar Davis, Samuel Kessler, Mircea Petrache, Ismail Ceylan, Michael Bronstein, Joey Bose , 2024

4. Generative flows on discrete state-spaces: Enabling multimodal flows with applications to protein co-design arXiv

   Andrew Campbell, Jason Yim, Regina Barzilay, Tom Rainforth, Tommi Jaakkola , 2024

5. Defog: Discrete flow matching for graph generation arXiv

   Yiming Qin, Manuel Madeira, Dorina Thanou, Pascal Frossard , 2024

6. Flow matching with general discrete paths: A kinetic-optimal perspective ICLR 2025 Oral

   Neta Shaul, Itai Gat, Marton Havasi, Daniel Severo, Anuroop Sriram, Peter Holderrieth, Brian Karrer, Yaron Lipman, Ricky T. Q. Chen , 2024

Simplex

1. Dirichlet flow matching with applications to DNA sequence design ICML 2024

   Hannes Stark, Bowen Jing, Chenyu Wang, Gabriele Corso, Bonnie Berger, Regina Barzilay, Tommi Jaakkola , 2024

2. Mixed continuous and categorical flow matching for 3D de novo molecule generation arXiv

   Ian Dunn, David Ryan Koes , 2024

3. Gumbel-softmax flow matching with straight-through guidance for controllable biological sequence generation arXiv

   Sophia Tang, Yinuo Zhang, Alexander Tong, Pranam Chatterjee , 2025

Bio Sequence Modeling

DNA Sequence

1. Fisher flow matching for generative modeling over discrete data NeurIPS 2024

   Oscar Davis, Samuel Kessler, Mircea Petrache, Ismail Ceylan, Michael Bronstein, Joey Bose , 2024

2. Dirichlet flow matching with applications to DNA sequence design arXiv

   Hannes Stark, Bowen Jing, Chenyu Wang, Gabriele Corso, Bonnie Berger, Regina Barzilay, Tommi Jaakkola , 2024

3. Gumbel-softmax flow matching with straight-through guidance for controllable biological sequence generation arXiv

   Sophia Tang, Yinuo Zhang, Alexander Tong, Pranam Chatterjee , 2025

4. Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design arXiv Tong Chen, Yinuo Zhang, Sophia Tang, Pranam Chatterjee , 2025

RNA Sequence

1. RNACG: A universal RNA sequence conditional generation model based on flow-matching arXiv

   Lei Gao, Zhi John Lu , 2024

2. RNAFlow: RNA structure & sequence design via inverse folding-based flow matching ICML 2024

   Divya Nori, Wengong Jin , 2024

3. RiboGen: RNA sequence and structure co-generation with equivariant multiflow arXiv

   Daniel Rubin, Alex de Souza Costa, Manvitha Ponnapati, Joseph Jacobson , 2025

4. RiboFlow: Conditional De Novo RNA Co-Design via Synergistic Flow Matching NeurIPS 2025

   Runze Ma, Zhongyue Zhang, Zichen Wang, Chenqing Hua, Jiahua Rao, Zhuomin Zhou, Shuangjia Zheng , 2025

Whole-Genome

1. GeNOT: Entropic (Gromov) Wasserstein flow matching with applications to single-cell genomics NeurIPS 2024

   Dominik Klein, Théo Uscidda, Fabian Theis, Marco Cuturi , 2024

2. CellFlow: A generative flow-based model for single-cell count data ICLR 2024 Workshop

   Antonio Palma, Till Richter, Hao Zhang, Andrea Dittadi, Fabian J. Theis , 2024

3. Multi-modal and multi-attribute generation of single cells with CFGen ICLR 2025

   Antonio Palma, Till Richter, Hao Zhang, Martin Lubetzki, Alexander Tong, Andrea Dittadi, Fabian J. Theis , 2025

Antibody Sequence

4. IgFlow: Flow Matching for de novo Antibody Design NeurIPS 2024

   S. Nagaraj, A. Shanehsazzadeh, H. Park, J. King, S. Levine , 2024

5. DyAB: Flow Matching for Flexible Antibody Design with AlphaFold-driven Pre-binding Antigen AAAI 2025

   C. Tan, Y. Zhang, Z. Gao, Y. Huang, H. Lin, L. Wu, F. Wu, M. Blanchette, S. Z. Li , 2025

Molecule Generation and Design

2D Molecule Generation

6. Improving Molecular Graph Generation with Flow Matching and Optimal Transport arXiv 2024

   X. Hou, T. Zhu, M. Ren, D. Bu, X. Gao, C. Zhang, S. Sun , 2024

7. Variational Flow Matching for Graph Generation NeurIPS 2024

   F. Eijkelboom, G. Bartosh, C. A. Naesseth, M. Welling, J. van de Meent , 2024

8. DeFoG: Discrete Flow Matching for Graph Generation ICML 2025

   Y. Qin, M. Madeira, D. Thanou, P. Frossard , 2025

3D Molecule Generation

SE(3)-equivariant

9. EquiFlow: Equivariant Conditional Flow Matching with Optimal Transport for 3D Molecular Conformation Prediction arXiv 2024

   Q. Tian, Y. Xu, Y. Yang, Z. Wang, Z. Liu, P. Yan, X. Li , 2024

10. Applications of Modular Co-Design for de novo 3D Molecule Generation NeurIPS 2024 Workshop

    D. Reidenbach, F. Nikitin, O. Isayev, S. G. Paliwal , 2024

11. Controlled Generation with Equivariant Variational Flow Matching ICML 2025

    F. Eijkelboom, H. Zimmermann, S. Vadgama, E. Bekkers, M. Welling, C. A. Naesseth, J.-W. van de Meent , 2025

12. ET-Flow: Equivariant Transformer Flow for Molecular Conformer Generation arXiv 2024

    M. Hassan, N. Shenoy, J. Lee, H. Stark, S. Thaler, D. Beaini , 2024

Efficiency

1. Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport (GOAT) ICLR 2025

   H. Hong, W. Lin, K. C. Tan , 2025

2. SemlaFlow—Efficient 3D Molecular Generation with Latent Attention and Equivariant Flow Matching AISTATS 2025

   R. Irwin, A. Tibo, J. P. Janet, S. Olsson , 2025

3. Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow ICML 2025

   Z. Cao, M. Geiger, A. D. S. Costa, D. Reidenbach, K. Kreis, T. Geffner, F. Pellegrini, G. Zhou, E. Kucukbenli , 2025

4. ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation NeurIPS 2024

   M. Hassan, N. Shenoy, J. Lee, H. Stärk, S. Thaler, D. Beaini , 2024

Guided Generation

1. 3D Structure Prediction of Atomic Systems with Flow-based Direct Preference Optimization NeurIPS 2024

   R. Jiao, X. Kong, W. Huang, Y. Liu , 2024

2. Extended Flow Matching: A Method of Conditional Generation with Generalized Continuity Equation arXiv 2024

   N. Isobe, M. Koyama, K. Hayashi, K. Fukumizu , 2024

3. Mixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generation arXiv 2024

   I. Dunn, D. R. Koes , 2024

4. Energy-Based Flow Matching for Generating 3D Molecular Structure ICML 2025

   W. Zhou, C. I. Sprague, V. Viliuga, M. Tadiello, A. Elofsson, H. Azizpour , 2025

5. Training-Free Guided Flow Matching with Optimal Control arXiv 2024

   L. Wang, C. Cheng, Y. Liao, Y. Qu, G. Liu , 2024

6. PropMolFlow: property-guided molecule generation with geometry-complete flow matching Nature Computational Science 2026

   Cheng Zeng, Jirui Jin, Connor Ambrose, George Karypis, Mark Transtrum, Ellad B. Tadmor, Richard G. Hennig, Adrian Roitberg, Stefano Martiniani, Mingjie Liu , 2026

Conditional Molecule Design and Applications

1. FlexSBDD: Structure-Based Drug Design with Flexible Protein Modeling NeurIPS 2024

   Z. Zhang, M. Wang, Q. Liu , 2024

2. Geometric Representation Condition Improves Equivariant Molecule Generation arXiv 2024

   Z. Li, C. Zhou, X. Wang, X. Peng, M. Zhang , 2024

3. Improving Structural Plausibility in 3D Molecule Generation via Property-Conditioned Training with Distorted Molecules bioRxiv 2024

   L. Vost, V. Chenthamarakshan, P. Das, C. M. Deane , 2024

4. Stiefel Flow Matching for Moment-Constrained Structure Elucidation arXiv 2024

   A. H. Cheng, A. Lo, K. L. K. Lee, S. Miret, A. Aspuru-Guzik , 2024

5. Template-Guided 3D Molecular Pose Generation via Flow Matching and Differentiable Optimization NeurIPS 2025

   Noémie Bergues, Arthur Carré, Paul Join-Lambert, Brice Hoffmann, Arnaud Blondel, Hamza Tajmouati , 2025

6. Prior-Guided Flow Matching for Target-Aware Molecule Design with Learnable Atom Number NeurIPS 2025

   Jingyuan Zhou, Hao Qian, Shikui Tu, Lei Xu , 2025

Unconditional Generation

Backbone Generation

1. Fast Protein Backbone Generation with SE(3) Flow Matching arXiv 2023

   J. Yim, A. Campbell, A. Y. Foong, M. Gastegger, J. Jiménez-Luna, S. Lewis, V. G. Satorras, B. S. Veeling, R. Barzilay, T. Jaakkola, F. Noé , 2023

2. SE(3)-Stochastic Flow Matching for Protein Backbone Generation ICLR 2024

   A. J. Bose, T. Akhound-Sadegh, G. Huguet, K. Fatras, J. Rector-Brooks, C.-H. Liu, A. C. Nica, M. Korablyov, M. Bronstein, A. Tong , 2024

3. Robust and Reliable de novo Protein Design: A Flow-Matching-Based Protein Generative Model Achieves Remarkably High Success Rates bioRxiv 2025

   J. Yan, Z. Cui, W. Yan, Y. Chen, M. Pu, S. Li, S. Ye , 2025

4. Generating Highly Designable Proteins with Geometric Algebra Flow Matching NeurIPS 2024

   S. Wagner, L. Seute, V. Viliuga, N. Wolf, F. Gräter, J. Stühmer , 2024

5. Sequence-Augmented SE(3)-Flow Matching for Conditional Protein Backbone Generation NeurIPS 2024

   G. Huguet, J. Vuckovic, K. Fatras, E. Thibodeau-Laufer, P. Lemos, R. Islam, C.-H. Liu, J. Rector-Brooks, T. Akhound-Sadegh, M. Bronstein, A. Tong, A. J. Bose , 2024

6. Proteina: Scaling Flow-Based Protein Structure Generative Models ICLR 2025 Oral

   T. Geffner, K. Didi, Z. Zhang, D. Reidenbach, Z. Cao, J. Yim, M. Geiger, C. Dallago, E. Kucukbenli, A. Vahdat, et al. , 2025

7. ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids ICLR 2025

   H. Stark, B. Jing, T. Geffner, J. Yim, T. Jaakkola, A. Vahdat, K. Kreis , 2025

8. Atom-level enzyme active site scaffolding using RFdiffusion2 Nature Methods 2025

   Woody Ahern, Jason Yim, Doug Tischer, Saman Salike, Seth M. Woodbury, Donghyo Kim, Indrek Kalvet, Yakov Kipnis, Brian Coventry, Han Raut Altae-Tran, Magnus S. Bauer, Regina Barzilay, Tommi S. Jaakkola, Rohith Krishna, David Baker , 2025

Co-design Generation

1. Co-Design Protein Sequence and Structure in Discrete Space via Generative Flow (CoFlow) Bioinformatics 2025

   S. Yang, L. Ju, P. Cheng, J. Zhou, Y. Cai, D. Feng , 2025

2. An All-Atom Generative Model for Designing Protein Complexes (APM) ICML 2025

   R. Chen, D. Xue, X. Zhou, Z. Zheng, X. Zeng, Q. Gu , 2025

3. Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design (Multiflow) ICML 2024

   A. Campbell, J. Yim, R. Barzilay, T. Rainforth, T. Jaakkola , 2024

Conditional Generation

Motif-scaffolding

1. Improved Motif-Scaffolding with SE(3) Flow Matching arXiv 2024

   Jason Yim, Andrew Campbell, Emile Mathieu, Andrew Y. K. Foong, Michael Gastegger, José Jiménez-Luna, Sarah Lewis, Victor Garcia Satorras, Bastiaan S. Veeling, Frank Noé, Regina Barzilay, Tommi S. Jaakkola , 2024

2. EVA: Geometric Inverse Design for Fast Protein Motif-Scaffolding with Coupled Flow ICLR 2025 Yufei Huang, Yunshu Liu, Lirong Wu, Haitao Lin, Cheng Tan, Odin Zhang, Zhangyang Gao, Siyuan Li, Zicheng Liu, Yunfan Liu, Tailin Wu, Stan Z. Li , 2025

Pocket & Binder Design

1. Design of Ligand-Binding Proteins with Atomic Flow Matching arXiv 2024

   Junqi Liu, Shaoning Li, Chence Shi, Zhi Yang, Jian Tang , 2024

2. Harmonic Self-Conditioned Flow Matching for Joint Multi-Ligand Docking and Binding Site Design ICML 2024

   Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi Jaakkola , 2024

3. Generalized Protein Pocket Generation with Prior-Informed Flow Matching (PocketFlow) NeurIPS 2024

   Zaixi Zhang, Marinka Zitnik, Qi Liu , 2024

4. FlowBack: A Generalized Flow-Matching Approach for Biomolecular Backmapping JCIM 2025

   Michael S. Jones, Smayan Khanna, Andrew L. Ferguson , 2025

Structure Prediction

Conformer Prediction

1. AlphaFold Meets Flow Matching for Generating Protein Ensembles ICML 2024

   B. Jing, B. Berger, T. Jaakkola , 2024

2. P2DFlow: A Protein Ensemble Generative Model with SE(3) Flow Matching JCTC 2025

   Y. Jin, Q. Huang, Z. Song, M. Zheng, D. Teng, Q. Shi , 2025

3. FlowPacker: Protein Side-Chain Packing with Torsional Flow Matching Bioinformatics 2025

   J. S. Lee, P. M. Kim , 2025

4. EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations ICLR 2024

   Y.-L. Liao, B. Wood, A. Das, T. Smidt , 2023

5. Full-Atom Peptide Design based on Multi-modal Flow Matching ICML 2024

   J. Li, C. Cheng, Z. Wu, R. Guo, S. Luo, Z. Ren, J. Peng, J. Ma , 2024

Side-chain Packing

1. FlowPacker: Protein Side-Chain Packing with Torsional Flow Matching Bioinformatics 2025

   J. S. Lee, P. M. Kim , 2025

2. EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations arXiv 2023

   Y.-L. Liao, B. Wood, A. Das, T. Smidt , 2023

3. Full-Atom Peptide Design based on Multi-modal Flow Matching ICML 2024

   J. Li, C. Cheng, Z. Wu, R. Guo, S. Luo, Z. Ren, J. Peng, J. Ma , 2024

Docking Prediction

1. Harmonic Self-Conditioned Flow Matching for Joint Multi-Ligand Docking and Binding Site Design ICML 2024

   Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi Jaakkola , 2024

2. FlowDock: Geometric Flow Matching for Generative Protein-Ligand Docking and Affinity Prediction Bioinformatics 2025

   Alex Morehead, Jianlin Cheng , 2025

3. ForceFM: Enhancing Protein-Ligand Predictions through Force-Guided Flow Matching NeurIPS 2025

   Huanlei Guo, Song Liu, Bingyi Jing , 2025

Peptide and Antibody Generation

1. P2DFlow: A Protein Ensemble Generative Model with SE(3) Flow Matching JCTC 2025

   Y. Jin, Q. Huang, Z. Song, M. Zheng, D. Teng, Q. Shi , 2025

2. Full-Atom Peptide Design based on Multi-modal Flow Matching ICML 2024

   J. Li, C. Cheng, Z. Wu, R. Guo, S. Luo, Z. Ren, J. Peng, J. Ma , 2024

3. PPFlow: Target-Aware Peptide Design with Torsional Flow Matching bioRxiv 2024

   H. Lin, O. Zhang, H. Zhao, D. Jiang, L. Wu, Z. Liu, Y. Huang, S. Z. Li , 2024

4. Non-Linear Flow Matching for Full-Atom Peptide Design arXiv 2025

   D. Huang, S. Tu , 2025

5. ProtFlow: Fast Protein Sequence Design via Flow Matching on Compressed Protein Language Model Embeddings arXiv 2025

   Z. Kong, Y. Zhu, Y. Xu, H. Zhou, M. Yin, J. Wu, H. Xu, C.-Y. Hsieh, T. Hou, J. Wu , 2025

Other Biology Applications

Dynamic Cell Trajectory

1. GeNOT: Entropic (Gromov) Wasserstein Flow Matching with Applications to Single-Cell Genomics NeurIPS 2024

   Dominik Klein, Théo Uscidda, Fabian Theis, Marco Cuturi , 2024

2. CellFlux: Simulating Cellular Morphology Changes via Flow Matching ICML 2025

   Yuhui Zhang, Yuchang Su, Chenyu Wang, Tianhong Li, Zoe Wefers, Jeffrey Nirschl, James Burgess, Daisy Ding, Alejandro Lozano, Emma Lundberg, Serena Yeung-Levy , 2025

3. Metric Flow Matching for Smooth Interpolations on the Data Manifold NeurIPS 2024

   Kacper Kapuśniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael Bronstein, Avishek Joey Bose, Francesco Di Giovanni , 2024

4. Diversified Flow Matching with Translation Identifiability ICML 2025

   Sagar Shrestha, Xiao Fu , 2025

Bio-Image Generation

1. FlowSDF: Flow Matching for Medical Image Segmentation Using Distance Transforms arXiv 2024

   Lea Bogensperger, Dominik Narnhofer, Alexander Falk, Konrad Schindler, Thomas Pock , 2024

2. Flow Matching for Medical Image Synthesis: Bridging the Gap Between Speed and Quality arXiv 2025

   Milad Yazdani, Yasamin Medghalchi, Pooria Ashrafian, Ilker Hacihaliloglu, Dena Shahriari , 2025

3. Multimodal Straight Flow Matching for Accelerated MR Imaging Computers in Biology and Medicine 2024

   Daikun Zhang, Qiuyi Han, Yuzhu Xiong, Hongwei Du , 2024

Spatial Transcriptomics

1. Wasserstein Flow Matching: Generative Modeling over Families of Distributions ICML 2025

   Doron Haviv, Aram-Alexandre Pooladian, Dana Pe’er, Brandon Amos , 2025

2. Scalable Generation of Spatial Transcriptomics from Histology Images via Whole-Slide Flow Matching ICML 2025

   Tinglin Huang, Tianyu Liu, Mehrtash Babadi, Wengong Jin, Rex Ying , 2025

Neural Activities

1. Stream-level Flow Matching with Gaussian Processes ICML 2025

   Ganchao Wei, Li Ma , 2025

2. Flow Matching for Few-Trial Neural Adaptation with Stable Latent Dynamics ICML 2025

   Puli Wang, Yu Qi, Yueming Wang, Gang Pan , 2025

3. Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry NeurIPS 2025

   Antoine Collas, Ce Ju, Nicolas Salvy, Bertrand Thirion , 2025

Datasets and Software Tools

Table 5 and 6 in our survey paper Flow Matching Meets Biology and Life Science: A Survey.

Citations

Please cite the following paper if you find the resource helpful for your research:

@article{li2026flow,
  title={Flow matching meets biology and life science: a survey},
  author={Li, Zihao and Zeng, Zhichen and Lin, Xiao and Fang, Feihao and Qu, Yanru and Xu, Zhe and Liu, Zhining and Ning, Xuying and Wei, Tianxin and Liu, Ge and others},
  journal={npj Artificial Intelligence},
  volume={2},
  number={1},
  pages={17},
  year={2026},
  publisher={Nature Publishing Group UK London}
}

License

This project is licensed under the MIT License - see the LICENSE file for details.

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