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Context-specific Bayesian clustering for gene expression data
Yoseph Barash,
Nir Friedman
*
*
Corresponding author for this work
The Rachel and Selim Benin School of Engineering and Computer Science
Department of Immunology and Cancer Research
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peer-review
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Scopus citations
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Keyphrases
Transcription Factor
100%
Expression Pattern
100%
Binding Site
100%
Gene-based
100%
Genomic Data
100%
Gene Expression Data
100%
Bayesian Clustering
100%
Genetic Data
50%
Mathematical Model
50%
Joint Distribution
50%
Gene Regulation
50%
Search Methods
50%
Problem Analysis
50%
Synthetic Data
50%
Real-life Data
50%
Expression Level
50%
Probabilistic Model
50%
Functional Class
50%
Binding Experiment
50%
Biological Insight
50%
Transcription Factor Binding Sites
50%
Genome-wide Expression
50%
Computational Tools
50%
Putative Binding Site
50%
Recent Growth
50%
Real-life Analysis
50%
Bayesian Information Criterion
50%
Probability Model
50%
Combined Probability
50%
Mathematics
Bayesian
100%
Real Life
50%
Joint Distribution
50%
Synthetic Data
50%
Mathematical Modeling
50%
Probability Model
50%
Computer Science
Pattern Expression
100%
Gene Expression Data
100%
Joint Distribution
50%
Expression Level
50%
Synthetic Data
50%
Biochemistry, Genetics and Molecular Biology
Binding Site
100%
Gene Expression Data
100%
Transcription Factors
75%
Genetics
25%
Gene Control
25%