zebrafish research with deep learning

Deep learning is now used in every research field, and zebrafish research is no exception. I’m just jotting down some papers, results of a quick search.

Behavioral analysis papers using deep learning

  1. Marigold: a machine learning-based web app for zebrafish pose tracking Gregory Teicher, R. Madison Riffe, Wayne Barnaby, Gabrielle Martin, Benjamin E. Clayton, Josef G. Trapani & Gerald B. Downes BMC Bioinformatics volume 26, Article number: 30 (2025) https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-025-06042-2 https://downeslab.github.io/marigold/
  2. Exploring the use of deep learning models for accurate tracking of 3D zebrafish trajectories Yi-Ling Fan,Yi-Ling Fan1,2Ching-Han HsuChing-Han Hsu2Fang-Rong HsuFang-Rong Hsu3Lun-De Liao Lun-De Liao1* Front. Bioeng. Biotechnol., 25 September 2024 Sec. Biosensors and Biomolecular Electronics Volume 12 – 2024 | https://doi.org/10.3389/fbioe.2024.1461264
  3. The Application of Artificial Intelligence to Support Behavior Recognition by Zebrafish: A Study Based on Deep Learning Models. Fan, YL., Hsu, FR., Lu, JY., Chung, MJ., Chang, TC. (2024). In: Hung, J.C., Yen, N., Chang, JW. (eds) Frontier Computing on Industrial Applications Volume 4. FC 2023. Lecture Notes in Electrical Engineering, vol 1134. Springer, Singapore. https://doi.org/10.1007/978-981-99-9342-0_27  深層学習YOLOv7モデルを利用したゼブラフィッシュの行動解析 本文有料
  4. Quantifying Variability in Zebrafish Larvae Locomotor Behavior across Experimental Conditions: A Learning-Based Tracker by Zhuo Zhang 1ORCID,Xinyu Chai 2,Guoning Si 2ORCID andXuping Zhang 3,* Fishes 2024, 9(6), 193; https://doi.org/10.3390/fishes9060193 利用したモデルはYou Look Only Once (YOLOv5) とDeep Simple Online Real Time Tracking (DeepSORT)
  5. Social behavioral profiling by unsupervised deep learning reveals a stimulative effect of dopamine D3 agonists on zebrafish sociality Author links open overlay panel Yijie Geng 1 , Christopher Yates 1 , Randall T. Peterson Cell Reports Methods Volume 3, Issue 1, 23 January 2023, 100381 Cell Reports Methods Article https://www.sciencedirect.com/science/article/pii/S2667237522002867?via%3Dihub

Other behavioral papers

  1. Linking Brain and Behavior States in Zebrafish Larvae Locomotion using Hidden Markov Models Mattéo Dommanget-Kott, Jorge Fernandez-de-Cossio-Diaz, Monica Coraggioso, Volker Bormuth, Rémi Monasson, Georges Debrégeas,Simona Cocco doi: https://doi.org/10.1101/2024.11.22.624881
  2. Precise visuomotor transformations underlying collective behavior in larval zebrafish Roy Harpaz, Minh Nguyet Nguyen, Armin Bahl & Florian Engert Nature Communications volume 12, Article number: 6578 (2021) https://www.nature.com/articles/s41467-021-26748-0
  3. Probabilistic Models of Larval Zebrafish Behavior Reveal Structure on Many Scales Robert Evan Johnson 1, Scott Linderman 2, Thomas Panier 3, Caroline Lei Wee 4, Erin Song 5, Kristian Joseph Herrera 5, Andrew Miller 6, Florian Engert 5 Curr Biol . 2020 Jan 6;30(1):70-82.e4. doi: 10.1016/j.cub.2019.11.026. Epub 2019 Dec 19.
  4. A 2D virtual reality system for visual goal-driven navigation in zebrafish larvae Adrien Jouary, Mathieu Haudrechy, Raphaël Candelier & German Sumbre Scientific Reports volume 6, Article number: 34015 (2016) https://www.nature.com/articles/srep34015

Other papers that used deep learning

  1. Deep learning dives: Predicting anxiety in zebrafish through novel tank assay analysis Author links open overlay panel Anagha Muralidharan a , Amrutha Swaminathan a , Alwin Poulose b Physiology & Behavior Volume 287, 1 December 2024, 114696 Physiology & Behavior https://www.sciencedirect.com/science/article/abs/pii/S0031938424002440
  2. Uncovering developmental time and tempo using deep learning Nikan Toulany, Hernán Morales-Navarrete, Daniel Čapek, Jannis Grathwohl, Murat Ünalan & Patrick Müller Nature Methods volume 20, pages2000–2010 (2023) https://www.nature.com/articles/s41592-023-01873-4　ゼブラフィッシュの胚の表現型と７つの主要なセルシグナリング経路との自動関連づけ
  3. EmbryoNet: using deep learning to link embryonic phenotypes to signaling pathways Daniel Čapek, Matvey Safroshkin, Hernán Morales-Navarrete, Nikan Toulany, Grigory Arutyunov, Anica Kurzbach, Johanna Bihler, Julia Hagauer, Sebastian Kick, Felicity Jones, Ben Jordan & Patrick Müller Nature Methods volume 20, pages815–823 (2023)　https://www.nature.com/articles/s41592-023-01873-4
  4. Automated staging of zebrafish embryos with deep learning Rebecca A Jones 1,2, Matthew J Renshaw 3, David J Barry 3, Life Sci Alliance. 2023 Oct 26;7(1):e202302351. doi: 10.26508/lsa.202302351 https://pmc.ncbi.nlm.nih.gov/articles/PMC10602791/ 胚発生の時期を自動判別
  5. Assessing Cardiac Functions of Zebrafish from Echocardiography Using Deep Learning 2023 Huang, Mao-HsiangAdvisor(s): Cao, Hung https://escholarship.org/uc/item/49g7b3ws
  6. Deep Fish: Deep Learning–Based Classification of Zebrafish Deformation for High-Throughput Screening Author links open overlay panel Omer Ishaq 1 * , Sajith Kecheril Sadanandan 1 * , Carolina Wählby 1　SLAS Discovery Volume 22, Issue 1, January 2017, Pages 102-107 SLAS Discovery Technical Notes 　https://www.sciencedirect.com/science/article/pii/S2472555222069313　胚スループットスクリーニングのための発生異常（奇形）の自動判定

 

 

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