is proposed and a
model for finding pathological formations based on machine learning methods is developed
Baltina, L.A.,
Hour, M.-J.,
Liu, Y.-C.,
Chang, Y.-S.,
Huang, S.-H.,
Lai, H.-C.,
Kondratenko, R.M.,
Petrova, S.F.,
Yunusov, M.S.,
Lin, C.-W. (2021) with the docking
models. Compounds 13 and 14 also had a strong interaction with the active site pocket of NS5 MTase
Gatiatulinaa, E.R.,
Popova, E.V.,
Polyakova, V.S.,
Skalnaya, A.A.,
Agletdinovd, E.F.,
Nikonorovae, A.A.,
Skalnyefgh, A.V.,
Tinkov, A.A. (2017) EVALUATION OF TISSUE METAL AND TRACE ELEMENT CONTENT IN A RAT
MODEL OF NON-ALCOHOLIC FATTY LIVER