gene microarray data set
Gene set analysis methods applied to chicken microarray expression data
... To adjust for multiple testing we applied FDR to the dif- ferent gene set tests. After adjustment most methods had no terms with p-value below 0.05 for all categories of GO terms, the exception being ...
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Using gene subsets in the assessment of microarray data quality for time course experiments
... cleotide microarray data. They are all based on the whole set of genes in the ...many data examples can be found in Brettschneider et ...The microarray data needs to be ...and ...
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Classification approaches for microarray gene expression data analysis
... Neural Networks (NNs) have been effectively used in numerous fields: control field, speech recognition, medical diagnosis, signal and image processing, etc. The main advantages of NNs include self-adaptivity, ...
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Detect Key Gene Information in Classification of Microarray Data
... a set of new basis is normally chosen for the ...from microarray data; linear discriminant analysis (LDA) is used to extract discriminant information from microarray ...
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Cluster Rasch models for microarray gene expression data
... assess gene expression profiles in a set of 60 human cancer cell lines that have been characterized pharmacologically by treatment with more than 70,000 different drug agents, one at time and ...in ...
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An Effective Validation Methodology of Proximity Measures for Clustering Gene Expression Microarray Data
... the data mining process to reveal natural structures and identify interesting patterns in the underlying ...given data set into groups based on specified features so that the data points ...
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Identification of disease causing genes using microarray data mining and gene ontology
... each gene separately and the interaction of genes are ...selected gene set may have ...successful gene selection methods because it considers the interaction of genes and it can remove ...
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Microarray data analysis: From hypotheses to conclusions using gene expression data
... the data set at hand, because one has so many ‘predictors’ (all the genes) and usu- ally relatively few ‘outcomes’ (class label of the sam- ...learning set (used to build the classifier) and test ...
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Using bayesian networks to construct gene regulatory networks from microarray data
... membina gene regulatory networks dari kitar sel S. cerevisiae set data disebabkan keupayaannya untuk mengendali set data microarray yang mempunyai nilai-nilai yang ...membina ...
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Analysis of Gene Expression Microarray Time Series Data
... the set of pooled standard ...for gene-specific variance components based on the James–Stein estimator and have used it to construct a test ...within gene variances are drawn from an inverse gamma ...
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Novel approaches to biclustering and gene functional classification in microarray gene expression data
... Cheng and Church evaluated their greedy biclustering algorithm using a subset of the yeast cell cycle dataset generated by (Cho et al., 1998) and a human lymphoma dataset (Alizadeh et al., 2000). They were able to ...
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A Novel Approach to Missing Data Estimation Technique for Microarray Gene Expression Data and Dimensionality Reduction
... Abstract: Microarray gene expression data analysis is one of the finest areas of gene expression analysis, where each gene with its expression value is useful to decide the future ...
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Identification of disease-causing genes using microarray data mining and Gene Ontology
... each gene separately and the interaction of genes are ...selected gene set may have ...successful gene selection methods because it considers the interaction of genes and it can remove ...
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Microarray Data Mining and Gene Regulatory Network Analysis
... of gene regulatory network is yet another major application of analysis of gene expression ...of gene regulatory ...that microarray expression data can be used to make predictions about ...
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A balanced iterative random forest for gene selection from microarray data
... the gene selec- tion ...training set into a new training set and a valida- tion set, which is used in the genes selection process to decide when to ...training set, the same genes are ...
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Data Complexity in Clustering Analysis of Gene Microarray Expression Profiles
... yeast gene cell cycle microarray expression profiles and dis- covered 24 large quality ...each gene, a cluster seeded by this gene is ...the gene that minimizes the increase in clus- ter ...
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Making microarray and RNA-seq gene expression data comparable
... for microarray and RNA-seq gene expression measurements from the highest expressed to the lowest ...RNA-seq gene expression values by microarray gene expression values from the second ...
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An Iterative Feature Perturbation Method for Gene Selection from Microarray Data
... one gene, using three filters: the t-test [5, 16], information gain [67], and ReliefF ...This gene filtering was performed within the 10-fold cross validation process (actually 200 reduced datasets were ...
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Predicting qualitative phenotypes from microarray data – the Eadgene pig data set
... selected gene are obtained by computing the correlation between the latent variables vectors and the whole data set ...two gene lists). This may infer that each gene lists is related to ...
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Apriori Gene Set-based Microarray Analysis for Disease Classification Using Unlabeled Data
... five gene sets were used for comparison, in order to choose the most informative gene sets for activity ...calculate gene set activity of each gene set, the gene members ...
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