Glazyrin, Y.E.; Veprintsev, D.V.; Ler, I.A.; Rossovskaya, M.L.; Varygina, S.A.; Glizer, S.L.; Zamay, T.N.; Petrova, M.M.; Minic, Z.; Berezovski, M.V.;
et al. Proteomics-Based Machine Learning Approach as an Alternative to Conventional Biomarkers for Differential Diagnosis of Chronic Kidney Diseases. Int. J. Mol. Sci. 2020, 21, 4802.
https://doi.org/10.3390/ijms21134802
AMA Style
Glazyrin YE, Veprintsev DV, Ler IA, Rossovskaya ML, Varygina SA, Glizer SL, Zamay TN, Petrova MM, Minic Z, Berezovski MV,
et al. Proteomics-Based Machine Learning Approach as an Alternative to Conventional Biomarkers for Differential Diagnosis of Chronic Kidney Diseases. International Journal of Molecular Sciences. 2020; 21(13):4802.
https://doi.org/10.3390/ijms21134802
Chicago/Turabian Style
Glazyrin, Yury E., Dmitry V. Veprintsev, Irina A. Ler, Maria L. Rossovskaya, Svetlana A. Varygina, Sofia L. Glizer, Tatiana N. Zamay, Marina M. Petrova, Zoran Minic, Maxim V. Berezovski,
and et al. 2020. "Proteomics-Based Machine Learning Approach as an Alternative to Conventional Biomarkers for Differential Diagnosis of Chronic Kidney Diseases" International Journal of Molecular Sciences 21, no. 13: 4802.
https://doi.org/10.3390/ijms21134802
APA Style
Glazyrin, Y. E., Veprintsev, D. V., Ler, I. A., Rossovskaya, M. L., Varygina, S. A., Glizer, S. L., Zamay, T. N., Petrova, M. M., Minic, Z., Berezovski, M. V., & Kichkailo, A. S.
(2020). Proteomics-Based Machine Learning Approach as an Alternative to Conventional Biomarkers for Differential Diagnosis of Chronic Kidney Diseases. International Journal of Molecular Sciences, 21(13), 4802.
https://doi.org/10.3390/ijms21134802