[PDF] Top 20 Analysis of Gene Expression Profiles with Linear Mixed Models
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Analysis of Gene Expression Profiles with Linear Mixed Models
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Inferring Drosophila gap gene regulatory network: pattern analysis of simulated gene expression profiles and stability analysis
... We have compared parameters using T-tests and the aver- age circuit topology (see Table 3, 4 and 5). From Table 3, we see that the main difference between the two stable patterns is the strong hb autoactivation in the ... See full document
10
Power analysis for generalized linear mixed models in ecology and evolution
... power analysis can grossly mislead study design, we are not suggesting that many researchers would be so na € ...power analysis at ...power analysis, or at least a justification of its ...power ... See full document
10
Prognostic factor analysis for breast cancer using gene expression profiles
... defined gene sets, we used the maximal clique algorithm [15] with Pearson correlation coefficient ...high/low expression gene sets which have over 15 independent ...high-expressed gene groups ... See full document
9
Warped linear mixed models for the genetic analysis of transformed phenotypes
... with linear Gaussian models 28,29 (Supplementary ...comparative analysis with transformations fit by WarpedLMM confirmed that the semi-parametric approach proposed by Zhou and Stephens is appropriate ... See full document
8
Comprehensive analysis of DNA methylation and gene expression profiles in cholangiocarcinoma
... by regulating the chromatin structure. Methylation of CpG islands can impair transcription factor binding, recruit repressive methyl-binding proteins, and stably silence gene expression [31]. Thus, CpG ... See full document
13
ADH genes were examined. ADH mRNA expression level was markedly reduced in HBV-related HCC tumor tissue. ADH1C and ADH5 overexpres-
... (ADH) expression is associated with cancer ...ADH gene expression in hepatitis B virus (HBV)-related hepato- cellular carcinoma ...Microarray analysis and survival profiles of ... See full document
22
Application of Hierarchical Linear Models/Linear Mixed effects Models in School Effectiveness Research
... this analysis, 100 out of 1003 schools were randomly ...regression models (disaggration, aggregation, and HLMs/LMEs) were fit to this subset of NELS-88 ...regression models at student level and ... See full document
8
Gene Set Enrichment Analysis using Linear Models and Diagnostics
... Looking for aneuploidy signals in the dataset is more akin to a general outlier search. It is known that extra DNA copies do lead in general to higher expression levels, however the relationship is weaker than ... See full document
6
Gene Set Enrichment Analysis using Linear Models and Diagnostics
... chromosome-level expression differences is ...observed expression differences for non-autosomal Y chromosome genes can serve several functions at once: a test of microarray technology, a test of GSEA ... See full document
7
Gene specific patterns of expression variation across organs and species
... of expression variance explained by species (x-axis) and by organs (y-axis) for each of the 6283 orthologous genes (dots) using linear ...whose expression varies considerably across species and ... See full document
13
Stable Graphical Models
... network models of gene expression profiles are a popular tool (Friedman et ...network models of gene expression involves learning linear regression- based Gaussian ... See full document
36
A comprehensive genome-wide profiling comparison between HBV and HCV infected hepatocellular carcinoma
... both expression and methylation levels were HLA-A, STAT1, and OAS2 ...HLA-A gene is closely re- lated to the immune response pathway and the diversity of HLA-A is a protective shield against bacterial and ... See full document
10
Analysis of melanopsin gene expression in the rabbit retina at different ages.
... the expression of melanopsin in the rabbit retina, even though rabbit pups (kits) have been viewed as an excellent natural model of synchronization of rhythms by food and its posterior shift to photoentrainment ... See full document
6
PM2.5 metal exposures and nocturnal heart rate variability: a panel study of boilermaker construction workers
... Particulate matter exposure assessment and analysis Personal, integrated, gravimetric samples were collected over the duration of the work shift using a KTL cyclone (GK2.05SH, BGI Incorporated, Waltham, MA) with ... See full document
8
Some problems in estimation in mixed linear models
... Linear models with multiple sources of error, known as mixed linear models, are used for modelling data from many scientific ...in mixed linear models, the ... See full document
163
Random Effect Selection in Linear Mixed Models.
... cannot say which criterion is better than the others. However, we can consider the behavior of these criteria as follows. When N > e 2 , BIC penalizes larger models more heavily, and hence it prefers simpler ... See full document
162
Generalized linear mixed models for count data
... Theoretically, the EM algorithm is the most accurate method that we have dis- cussed so far. Unlike the Laplace approximation and Gauss-Hermite quadrature, where we have to worry about the coefficients of the error terms ... See full document
97
Activity of the Bacillus anthracis20 kDa protective antigen component
... Expression profile of genes related to the cell adhe- sion pathway that were up regulated by rPA 20 in PBMC. Cells were incubated with the rPA 20 for 4 hrs. RNA samples were isolated and hybridized on the cDNA ... See full document
14
Estimation for Multivariate Linear Mixed Models
... applied linear mixed model in Statistics for Biology Systems to calculate both covariates and correlations between signals which followed non-stationary time ...multivariate mixed ordinal and ... See full document
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