APA (7th ed.) Citation

Xu, Q., Ma, L., Streuer, A., Altrock, E., Schmitt, N., Rapp, F., . . . Riabov, V. (2025). Machine learning-based in-silico analysis identifies signatures of lysyl oxidases for prognostic and therapeutic response prediction in cancer. Cell communication and signaling, 23(1), 169-17. https://doi.org/10.1186/s12964-025-02176-1

Chicago Style (17th ed.) Citation

Xu, Qingyu, et al. "Machine Learning-based In-silico Analysis Identifies Signatures of Lysyl Oxidases for Prognostic and Therapeutic Response Prediction in Cancer." Cell Communication and Signaling 23, no. 1 (2025): 169-17. https://doi.org/10.1186/s12964-025-02176-1.

MLA (9th ed.) Citation

Xu, Qingyu, et al. "Machine Learning-based In-silico Analysis Identifies Signatures of Lysyl Oxidases for Prognostic and Therapeutic Response Prediction in Cancer." Cell Communication and Signaling, vol. 23, no. 1, 2025, pp. 169-17, https://doi.org/10.1186/s12964-025-02176-1.