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QSAR MODELLING OF THYMIDYLATE SYNTHASE INHIBITORS IN A SERIES OF QUINAZOLINE DERIVATIVES
KHAIRULLINA, V.R., GERCHIKOV, A.Y., LAGUNIN, A.A., ZARUDII, F.S. (2018)
range 0.52 – 24,800.00 nM. Statistically significant QSAR models were constructed using MNA- and QNA
QSAR MODELLING OF THYMIDYLATE SYNTHASE INHIBITORS IN A SERIES OF QUINAZOLINE DERIVATIVES
Khairullina, V.R., Gerchikov, A.Ya., Lagunin, A.A., Zarudii, F.S. (2017)
range 0.52 – 24,800.00 nM. Statistically significant QSAR models were constructed using MNA- and QNA
QSAR-МОДЕЛИРОВАНИЕ СВЯЗИ "СТРУКТУРА - АНТИОКИСЛИТЕЛЬНАЯ АКТИВНОСТЬ" В РЯДУ НЕКОТОРЫХ ПРОИЗВОДНЫХ БЕНЗОПИРАНА И БЕНЗОФУРАНА
QSAR-MODELING OF THE RELATIONSHIP "STRUCTURE - ANTIOXIDATIVE ACTIVITY" IN A SERIES OF SOME BENZOPIRANE AND BENZOFURANE DERIVATIVES
МАРТЫНОВА, Ю.З., ХАЙРУЛЛИНА, В.Р., ГАРИФУЛЛИНА, Г.Г., МИЦУКОВА, Д.С., ЗАРУДИЙ, Ф.С., МУСТАФИН, А.Г., Martynova, Yu. Z., Khairullina, V.R., Garifullina, G.G., Mitsukova, D.S., Zarudiy, F.S., Mustafin, A.G. (2019)
QSAR-MODELING OF THE RELATIONSHIP "STRUCTURE - ANTIOXIDATIVE ACTIVITY" IN A SERIES OF SOME
QUANTITATIVE ANALYSIS OF STRUCTURE−ACTIVITY RELATIONSHIPS OF TETRAHYDRO2HISOINDOLE CYCLOOXYGENASE2 INHIBITORS
Khayrullina, V.R., Gerchikov, A.Ya., Lagunin, A.A., Zarudii, F.S. (2015)
values. Six statistically significant consensus QSAR models for prediction of IC50 values were designed
QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIP OF THE THYMIDYLATE SYNTHASE INHIBITORS OF MUS MUSCULUS IN THE SERIES OF QUINAZOLIN-4-ONE AND QUINAZOLIN-4-IMINE DERIVATIVES
KHAIRULLINA, V.R., GERCHIKOV, A.Y., MUSTAFIN, A.G., GIMADIEVA, A.R., ZARUDII, F.S. (2018)
and QNAdescriptors using the self-consistent regression, 6 statistically significant consensus models
QSРR-МОДЕЛИРОВАНИЕ АНТИОКИСЛИТЕЛЬНОЙ АКТИВНОСТИ ПОТЕНЦИАЛЬНЫХ И ПРОМЫШЛЕННО ИСПОЛЬЗУЕМЫХ СТАБИЛИЗАТОРОВ ИЗ КЛАССА ЗАМЕЩЕННЫХ АЛКИЛФЕНОЛОВ
QSPR-MODELING OF ANTIOXIDANT ACTIVITY OF POTENTIAL AND INDUSTRIAL USED STABILIZERS FROM THE CLASS OF SUBSTITUTED ALKYLPHENOLS
МАРТЫНОВА, Ю.З., ХАЙРУЛЛИНА, В.Р., ГЕРЧИКОВ, А.Я., ЗАРУДИЙ, Ф.С., МУСТАФИН, А.Г., MARTYNOVA, YU. Z., KHAIRULLINA, V.R., GERCHIKOV, A. YA., ZARUDIY, F.S., MUSTAFIN, A.G. (2020)
QSPR-MODELING OF ANTIOXIDANT ACTIVITY OF POTENTIAL AND INDUSTRIAL USED STABILIZERS FROM THE CLASS
Fractional Levy stable motion: Finite difference iterative forecasting model
Liu, H., Song, W., Li, M., Kudreyko, A., Zio, E. (2020)
forecasting model with Long Range Dependent (LRD) characteristics. The LRD forecasting model considers
DETERMINATION OF THE VOLUME OF EARLY HYPOTONIC HEMORRHAGE BY 3D MODELING OF ULTRASOUND INVESTIGATION RESULTS
ZIGANSHIN, A.M., MUDROV, V.A., LYAPUNOV, A.K. (2020)
. The method is based on clinical application of 3D modeling of results obtained by ultrasound investigations
An iterative model of the generalized Cauchy process for predicting the remaining useful life of lithium-ion batteries
Hong, G., Song, W., Gao, Y., Zio, E., Kudreyko, A. (2022)
). In this paper, an iterative model of the generalized Cauchy (GC) process with LRD characteristics is proposed
User-level malicious behavior analysis model based on the NMF-GMM algorithm and ensemble strategy
Kan, Xiu, Fan, Yixuan, Zheng, Jinjie, Kudreyko, Aleksey, Chi, Chi-hung, Song, Wanqing, Tregubova, Albina (2023)
-level malicious behavior analysis model is established based on non-negative matrix factorization-Gaussian mixture

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