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1 fers several tools including a sophisticated multifactor analysis of relevant physicochemical propert
2  dry air, and pulmonary disease mechanics by multifactor analysis of variance.
3  and disappointing dead ends, indicating the multifactored and complex nature of the disorder.
4      Data were subjected to evaluation using multifactor ANOVA and principal component analysis (PCA)
5                                              Multifactor ANOVA revealed that levels of those volatile
6                                              Multifactor ANOVA, considering the content of total anth
7 tail plays a stimulatory role in cooperative multifactor assembly.
8 95% confidence intervals obtained by using a multifactor bootstrap-resampling approach contain the tr
9 val around the calculated time by applying a multifactor bootstrap-resampling approach.
10 expression changes were driven by a stepwise multifactor cascading control mechanism, where the speci
11                                              Multifactor ChIP-Seq analysis in primary human cells cou
12 Thus, NAP-1 appears to be one component of a multifactor chromatin assembly machinery that mediates t
13                          However, multisite, multifactor climate manipulation studies that have exami
14 mains that have been implicated in the yeast multifactor complex (eIF1-eIF3-eIF5-eIF2-GTP-Met-tRNA(i)
15 erated from purified human proteins a stable multifactor complex (MFC) comprising eIF1, eIF2, eIF3 an
16 tions that disrupt eIF2-eIF3 contacts in the multifactor complex (MFC) diminished 40S-bound TC, indic
17 e eIF2.tRNA(i)(Met.)GTP complex (TC) and the multifactor complex (MFC) required for translation initi
18           Initiation factor 3 (eIF3) forms a multifactor complex (MFC) with eIF1, eIF2, and eIF5 that
19   It is recruited to the 43 S complex in the multifactor complex (MFC) with eIF2, eIF3, and eIF5 via
20  (eIF3) of Saccharo myces cerevisiae forms a multifactor complex (MFC) with eIFs 1, 2, 5 and Met-tRNA
21 nd eIF3c, thereby mediating formation of the multifactor complex (MFC), an important intermediate for
22 duced 40S binding of all constituents of the multifactor complex (MFC), comprised of these three fact
23 binds the eIF3/eIF1/eIF5 complex to form the multifactor complex (MFC), whereas eIF2.GDP binds the pe
24 acts with eIF3-eIF1-eIF5 complex to form the multifactor complex (MFC), while eIF2GDP associates with
25 RNA(i)(Met) ternary complex (TC) to form the multifactor complex (MFC).
26 to, and stabilizes, the eIF3-eIF5- eIF1-eIF2 multifactor complex and is required for the normal level
27 to interact with eIF1, eIF2, and eIF3 in the multifactor complex and with eIF4G in the 48S complex.
28 C loading on 40S subunits or destabilize the multifactor complex containing eIF1, eIF3, eIF5, and TC,
29 F3, was shown to bind to, and stabilize, the multifactor complex containing eIFs 1, 2, 3, and 5 and M
30  interaction between eIF2 and eIF3/eIF1 in a multifactor complex containing Met-tRNA(i)(Met).
31  initiation factors are capable of forming a multifactor complex in vitro.
32 mutation in eIF5-CTD, which destabilizes the multifactor complex in vivo, reduced the binding of Met-
33                          We propose that the multifactor complex is an important intermediate in tran
34  to the silencer leads to the formation of a multifactor complex that induces silencer function and r
35 which mRNAs undergo polyadenylation; CPSF, a multifactor complex that interacts with the near-ubiquit
36                                          The multifactor complex was disrupted by the tif5-7A mutatio
37 ith CARM1, CBP, c-Jun, and Sp1 and that this multifactor complex was formed in a p53-dependent manner
38     It is recruited to the 40 S subunit in a multifactor complex with Met-tRNA(i)(Met), eIF2, eIF3, a
39 est the occurrence of an eIF3/eIF1/eIF5/eIF2 multifactor complex, which was observed in cell extracts
40  These results suggest that the stability of multifactor complexes at promoters and regulatory elemen
41 ted from a failure to treat job control as a multifactor concept.
42                         Here, we appeal to a multifactor construct, which allows the assessment of ou
43 cation, few have examined these effects in a multifactor context or recorded how these effects vary s
44 ntly, the context provided by multimodal, or multifactor delivery represents a key element of most bi
45 ly to characterize count data and allows for multifactor design.
46 mbinatorial approach, namely the generalized multifactor dimensionality reduction (GMDR) method, whic
47 ormed Neural Networks (NNs), and Model-based Multifactor Dimensionality Reduction (MB-MDR) models.
48 fied analysis, combined effect analysis, and multifactor dimensionality reduction (MDR) analysis.
49                The computationally efficient multifactor dimensionality reduction (MDR) approach has
50                                              Multifactor Dimensionality Reduction (MDR) has been intr
51                                              Multifactor dimensionality reduction (MDR) is a powerful
52 this problem, we have previously developed a multifactor dimensionality reduction (MDR) method for co
53 To address this problem, we have developed a multifactor dimensionality reduction (MDR) method for co
54 everal combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, have
55 Recent combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, the c
56 MDR-Phenomics, a novel approach based on the multifactor dimensionality reduction (MDR) method, to de
57 and BAT3) were investigated by entropy-based multifactor dimensionality reduction (MDR), classificati
58 f the AMBIENCE algorithm was compared to the multifactor dimensionality reduction (MDR), generalized
59  3.95, P = 7.8 x 10(-5) [FDR </=0.05], P for multifactor dimensionality reduction = 5.9 x 10(-45)).
60                   AMBROSIA was compared with multifactor dimensionality reduction across several dive
61                                   Subsequent multifactor dimensionality reduction and classification
62                                              Multifactor dimensionality reduction identified a gene-g
63 teractions were assessed through model-based multifactor dimensionality reduction in the PIAMA study,
64                                              Multifactor dimensionality reduction indicated that the
65                                     Parallel multifactor dimensionality reduction is a tool for large
66 modal random survival forest and generalized multifactor dimensionality reduction methods.
67                                              Multifactor dimensionality reduction revealed that genot
68                       FITF also outperformed multifactor dimensionality reduction when interactions i
69 ts show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Ful
70 o-head comparisons with the relevance-chain, multifactor dimensionality reduction, and PDT methods, t
71 o-head comparisons with the relevance-chain, multifactor dimensionality reduction, and the pedigree d
72 eotide polymorphisms (SNPs), haplotyping and multifactor dimensionality reduction.
73                                      We used Multifactor- dimensionality reduction (MDR) program as a
74 ve refined independent marker sets, extended multifactor-dimensionality reduction (EMDR) analysis was
75                                 We introduce multifactor-dimensionality reduction (MDR) as a method f
76 human diseases, such as Parkinson's disease, multifactor disorder and Type-II diabetes.
77 e, long-term ecosystem-scale studies testing multifactor effects on plants and soils are urgently req
78  These findings indicate the importance of a multifactor experimental approach to understanding ecosy
79 ariable climate and atmosphere simulator for multifactor experimentation on natural or artificial eco
80                                              Multifactor experiments are often advocated as important
81            Our goals were to investigate how multifactor experiments can be used to constrain models
82 ctive importance of these processes requires multifactor experiments under realistic field conditions
83                                          The multifactor gatekeeping model has been proposed to expla
84         In 2006, we established a long-term, multifactor global change experiment to determine the in
85       Much concern has been raised about how multifactor global change has affected food security and
86 n the longest-running, best-replicated, most-multifactor global-change experiment at the ecosystem sc
87                           We use a long-term multifactor grassland restoration experiment established
88                                We found that multifactor habitat suitability models performed better
89 es and profiles, which might be explained by multifactors including charge, size, helicity, hydrophob
90                                 A variety of multifactor indexes have been proposed for preoperative
91                    It is likely that optimal multifactor initiation complexes exist that allow for op
92 story of reflux is an important risk for EA, multifactor interactions also play important roles in EA
93 f analytical tools for identifying nonlinear multifactor interactions and unraveling the genetic arch
94                                  Determining multifactor interactions is the primary topic of interes
95                                   Widespread multifactor interactions present a significant challenge
96 ocesses may influence their responses to the multifactor interactions.
97 upervisors and 179 supervisees completed the Multifactor Leadership Questionnaire and a demographic s
98                                            A multifactor logistic regression analysis was performed t
99                                              Multifactor logistic regression analysis was used to ide
100 tions of soil carbon dynamics and results of multifactor manipulations to calibrate a model that can
101                                   Across all multifactor manipulations, elevated carbon dioxide suppr
102                     These results identify a multifactored mechanism to control LKB1 localization, an
103  trophic magnification factors (TMFs), and a multifactor model that included delta(15)N-derived troph
104  range overlap of environmental variables in multifactor models controlling for phylogeny to simultan
105                           We also found that multifactor models provided more concerning assessments
106 g the classification and prediction error of multifactor models.
107                       Herein, we developed a multifactor, multieffect, and multilevel meta-analytic m
108 on the magnitude of each interacting factor, multifactor, multilevel experiments are required, but ar
109 d revealed both single-factor monotropic and multifactor pleiotropic loci.
110                    We applied 10 TBMs to the multifactor Prairie Heating and CO2 Enrichment (PHACE) e
111  distinguish metazoan cells are specified by multifactor regulatory complexes containing distinct com
112 ngle factors (i.e., Ea or DeltaS alone); (2) multifactor scenarios of photosynthetic temperature accl
113 , these data reveal the power of integrating multifactor sequencing of chromatin immunoprecipitates w
114 er, our data demonstrate the requirement for multifactor signal integration by Arp2/3 complex and hig
115 tition, and more SGH research should feature multifactor stress.
116 perature ranges to determine whether and how multifactor thermal acclimation of photosynthesis occurs
117  by competing with activating ETS factors in multifactor transcriptional complexes.

 
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