using various statistical
algorithms and artificial intelligence. In particular, we suggest the use of a
Kan, Xiu,
Fan, Yixuan,
Zheng, Jinjie,
Kudreyko, Aleksey,
Chi, Chi-hung,
Song, Wanqing,
Tregubova, Albina (2023) User-level malicious behavior analysis model based on the NMF-GMM
algorithm and ensemble strategy
Sufianov, Albert,
Beilerli, Aferin,
Kudriashov, Valentin,
Ilyasova, Tatiana,
Wenjie, Bu,
Beylerli, Ozal (2023) Small interfering RNA (siRNAs) is a double-stranded RNA molecule which can
hybridize with a
organs, as well as the developed
algorithm for calculating the volume of inhomogeneity. To implement
algorithms for working with the proposed resources in the classroom and in the extracurricular time
Korytina, G.F.,
Aznabaeva, Y.G.,
Kochetova, O.V.,
Nasibullin, T.R.,
Akhmadishina, L.Z.,
Khusnutdinova, N.N.,
Zagidullin, N. Sh.,
Victorova, T.V. (2023) .34). Using the APSampler
algorithm, we obtained gene–gene combinations that remained significantly associated
Nasyrova, Regina F.,
Shnayder, Natalia A.,
Osipova, Sofia M.,
Khasanova, Aiperi K.,
Efremov, Ilya S.,
Al-Zamil, Mustafa,
Petrova, Marina M.,
Narodova, Ekaterina A.,
Garganeeva, Natalia P.,
Shipulin, German A. (2023) propose a riskometer for PTAP-PGx and a decision-making
algorithm for
psychiatrists. Conclusions