Generating a Mixed Model of Gene Expression Data
Factors affecting the accuracy of a class prediction model in gene expression data
... five gene expression microarray ...clustered data, where the selected stud- ies and the classification methods act as ...regression model [48]. The logistic random ef- fects model is ...
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Classical and Bayesian mixed model analysis of microarray data for detecting gene expression and DNA differences
... In this section, we describe the performance of our methods for the test of genotype-by- time interaction which is of primary interest in our application. Analogous results, including tables and figures, are presented ...
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Mixed-Model Reanalysis of Primate Data Suggests Tissue and Species Biases in Oligonucleotide-Based Gene Expression Profiles
... use gene expression profiling to identify genes that are associated with morphological, physiological, or behavioral divergence between species and whether these genes have undergone positive ...in ...
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Stability and bifurcation analysis of a gene expression model with small RNAs and mixed delays
... of gene information in reality, the time delay of the system is not invariable [21–23], and it may produce complicated nonlinear phe- nomena with the change of ...cases, gene regulatory networks with sRNA ...
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Model based cluster analysis of microarray gene expression data
... discussion Data and preprocessing Pneumococcal otitis media is one of the most common dis- eases in ...observed gene-expression levels so that they are more likely to have a normal distribution, ...
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Factors affecting the accuracy of a class prediction model in gene expression data
... the gene expression data, namely the number of differentially expressed genes, the fold changes and the within-class ...prediction model were statistically assessed by random effects logistic ...
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Neural network model of gene expression
... network model interprets gene interac- tions as connections between genes and the states of gene expression that can be either on or ...the gene control system as a network is identical ...
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Gene selection and classification in autism gene expression data
... between gene expression among the autistic and healthy ...in gene expression between the subtypes of autism such as autism with regression and without regression at the early onset ...
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An integrated semi supervised clustering model for time course gene expression data
... course data using basic conventional clustering methods often, present computational challenges and most algorithms are porn error when dealing with such data ...semi-supervised model for clustering ...
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Estimation of mixed-mode fracture parameters by gene expression programming
... In this section, by conducting genetic programming principles, a unique formula is inferred from the data for an arbitrary center crack. In these problems, a cen- ter crack with any inclination angle with respect ...
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Efficient Clustering for Gene Expression Data
... 2. RELATED WORK Jian Wen [10] in his biomedical literatures on ontology is useful to improve the performance of information retrieval. The method of ontology-based solves synonym problems with a new frame for genomic ...
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Techniques for clustering gene expression data
... The algorithm of Cheng and Church [15] (adapted from Hartigan [42]) ob- tains H-scores, (Eq. 1, Fig. 1) [10]) of the sub-matrices of the GE matrix. This method is initialised for the entire GE matrix and considers a ...
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Effective gene selection techniques for classification of gene expression data
... ABSTRAK Pembangunan teknologi microarray membolehkan penyelidik mengawal beribu-ribu tahap ekspresi gen dalam satu eksperimen microarray. Pengkelasan sampel tisu kepada tisu tumor atau tisu biasa merupakan salah satu ...
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Identifying Gene Regulatory Networks from Gene Expression Data
... Stochastic gene network models are especially appropriate for reconstructing gene net- works from expression data because of the inherent noise present in ...a gene is differentially ...
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Exploring gene expression and protein binding data for gene regulation
... ChIP-Seq data to improve results for the integrative analysis of protein binding and gene expression data has been ...ChIP-seq data of different proteins and markers, different peak- ...
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Toward a Neutral Evolutionary Model of Gene Expression
... stochastic model that describes neutral changes of gene expression over evolutionary time as a compound Poisson process where evolutionary events cause changes of expression level according to ...
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Bayesian hierarchical graph-structured model for pathway analysis using gene expression data
... 3.2 Simulation studies In this section, the data are generated based on a linear regression model Y = X T β+e. For each replicate, the size of the dataset, n, equals 100 for a training, a tuning and a test ...
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Gene expression profiling predicts a three-gene expression signature of endometrial adenocarcinoma in a rat model
... as gene expression profiling by DNA microarrays, provide unprecedented tools to handle the complexity of cancer at the transcriptional ...global expression data to identify potential ...
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Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data
... my mixed cell ...are mixed with cells of a different type to the kinetic parameter estimates when the cell populations are ...the mixed and pure cell populations are shown for CLP (A–C), GMP (D–F), ...
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Clustering gene expression data with repeated measurements
... different expression pat- terns between different types of ...and model-based approaches [8-10]) and many of these techniques have been applied to expression data (for example ...‘typical’ ...
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