Context-specific infinite mixtures for clustering gene expression profiles across diverse microarray dataset. - Wikidata - wikimedia - TriplyDB

Context-specific infinite mixtures for clustering gene expression profiles across diverse microarray dataset.

Context-specific infinite mixtures for clustering gene expression profiles across diverse microarray dataset.

http://www.wikidata.org/entity/Q38757632

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CLEAN: CLustering Enrichment ANalysis.Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data.Influence of fatty acid diets on gene expression in rat mammary epithelial cells Application of gene shaving and mixture models to cluster microarray gene expression data.Genomics Portals: integrative web-platform for mining genomics data.A semi-parametric Bayesian model for unsupervised differential co-expression analysis Discovering transcriptional modules by Bayesian data integration.WebGimm: An integrated web-based platform for cluster analysis, functional analysis, and interactive visualization of results.Joint modeling of longitudinal data and informative dropout time in the presence of multiple changepoints.Patient-specific data fusion defines prognostic cancer subtypes MDI-GPU: accelerating integrative modelling for genomic-scale data using GP-GPU computing.Bayesian correlated clustering to integrate multiple datasets.

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P2860

Context-specific infinite mixtures for clustering gene expression profiles across diverse microarray dataset.

http://www.wikidata.org/entity/Q38757632

description

2006 nî lūn-bûn

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2006年の論文

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2006年論文

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2006年論文

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2006年論文

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2006年論文

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2006年论文

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2006年论文

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name

Context-specific infinite mixt ...... ss diverse microarray dataset.

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Context-specific infinite mixt ...... ss diverse microarray dataset.

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Context-specific infinite mixt ...... ss diverse microarray dataset.

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Context-specific infinite mixt ...... oss diverse microarray dataset

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J Guo

http://www.w3.org/2001/XMLSchema#string

K Y Yeung

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Mario Medvedovic

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S Sivaganesan

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X Liu

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P2860

Cluster analysis and display of genome-wide expression patterns

Microarray analysis of gene expression during the cell cycle

The KEGG resource for deciphering the genome

Transcriptional regulatory networks in Saccharomyces cerevisiae

The core meiotic transcriptome in budding yeasts.

A genome-wide transcriptional analysis of the mitotic cell cycle

A gene-coexpression network for global discovery of conserved genetic modules

Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data

A mixture model-based approach to the clustering of microarray expression data.

Context-specific Bayesian clustering for gene expression data.

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1737-1744

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10.1093/BIOINFORMATICS/BTL184

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14

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22

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Roger E Bumgarner

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2006-05-18T00:00:00Z

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7071351

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