ZAGIDULLIN, N.SH.,
MOTLOCH, LUKAS J,,
GAREEVA, D.F.,
HAMITOVA, AYSILU,
LAKMAN, I.A.,
KRIONI, ILJA,
POPOV, DENIS,
ZULKARNEEV, R.KH.,
PAAR, VERA,
KOPP, KRISTEN,
JIRAK, PETER,
ISHMETOV, V.SH.,
HOPPE, UTA C.,
TULBAEV, EDUARD,
V.N. Pavlov (2020) .001). When two biomarkers were combined in a multivariate Cox regression
model, relevant improvement of
risk models. Linear regression analyses were performed to estimate the relationship between SNPs and lung
STARODUBOV, V.I.,
MARCZAK, L.B.,
VARAVIKOVA, E.,
BIKBOV, B.,
ERMAKOV, S.P.,
GALL, J.,
GLENN, S.D.,
GRISWOLD, M.,
IDRISOV, B.,
KRAVCHENKO, M.,
LIOZNOV, D.,
LOYOLA, E.,
RAKOVAC, I.,
VLADIMIROV, S.K.,
VLASSOV, V.,
MURRAY, C.J.L.,
NAGHAVI, M (2018) , and
Risk Factors Study 2016
(GBD 2016) to evaluate trends in mortality, causes of death, years lived
=0.008) and dominant (OR 0.41, PFDR 4.38×10−4
) genetic
model. The analysis of gene–gene
interactions
lncRNAs tested as potential therapeutic and diagnostic molecules in cells and animal
model experiments
forecasting
model with Long Range Dependent (LRD) characteristics. The LRD forecasting
model considers
.01) insulin, HOMA-IR (homeostasis
model assessment of insulin resistance, p=0.0019), hsCRP (p=0.036), waist