APA (7th ed.) Citation

M, K., J, W., D, F., S, R., FA, G., & E, R. (2026). Synthetic data enables human-grade microtubule analysis with foundation models for segmentation. PLoS computational biology, 22(5), e1013901. https://doi.org/10.1371/journal.pcbi.1013901

Chicago Style (17th ed.) Citation

M, Koddenbrock, Westerhoff J, Fachet D, Reber S, Gers FA, and Rodner E. "Synthetic Data Enables Human-grade Microtubule Analysis with Foundation Models for Segmentation." PLoS Computational Biology 22, no. 5 (2026): e1013901. https://doi.org/10.1371/journal.pcbi.1013901.

MLA (9th ed.) Citation

M, Koddenbrock, et al. "Synthetic Data Enables Human-grade Microtubule Analysis with Foundation Models for Segmentation." PLoS Computational Biology, vol. 22, no. 5, 2026, p. e1013901, https://doi.org/10.1371/journal.pcbi.1013901.