MDPI and ACS Style
Scebba, F.; Salvadori, S.; Cateni, S.; Mantellini, P.; Carozzi, F.; Bisanzi, S.; Sani, C.; Robotti, M.; Barravecchia, I.; Martella, F.;
et al. Top–Down Proteomics of Human Saliva, Analyzed with Logistic Regression and Machine Learning Methods, Reveal Molecular Signatures of Ovarian Cancer. Int. J. Mol. Sci. 2023, 24, 15716.
https://doi.org/10.3390/ijms242115716
AMA Style
Scebba F, Salvadori S, Cateni S, Mantellini P, Carozzi F, Bisanzi S, Sani C, Robotti M, Barravecchia I, Martella F,
et al. Top–Down Proteomics of Human Saliva, Analyzed with Logistic Regression and Machine Learning Methods, Reveal Molecular Signatures of Ovarian Cancer. International Journal of Molecular Sciences. 2023; 24(21):15716.
https://doi.org/10.3390/ijms242115716
Chicago/Turabian Style
Scebba, Francesca, Stefano Salvadori, Silvia Cateni, Paola Mantellini, Francesca Carozzi, Simonetta Bisanzi, Cristina Sani, Marzia Robotti, Ivana Barravecchia, Francesca Martella,
and et al. 2023. "Top–Down Proteomics of Human Saliva, Analyzed with Logistic Regression and Machine Learning Methods, Reveal Molecular Signatures of Ovarian Cancer" International Journal of Molecular Sciences 24, no. 21: 15716.
https://doi.org/10.3390/ijms242115716