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A Markov random field model for network-based analysis of genomic data
Zhi Wei
, Hongzhe Li
Research output
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Contribution to journal
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Article
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peer-review
196
Scopus citations
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Dive into the research topics of 'A Markov random field model for network-based analysis of genomic data'. Together they form a unique fingerprint.
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Keyphrases
Biological Processes
100%
Differentially Expressed Genes
100%
Breast Cancer
100%
Genomic Data
100%
Markov Random Field Model
100%
Markov Random Field
100%
Network-based Analysis
100%
Pathway Structure
100%
High Sensitivity
50%
Test Statistic
50%
False Discovery Rate
50%
Simulation Study
50%
Biological Networks
50%
Differentially Expressed
50%
Breast Cancer Survival
50%
Univariate Test
50%
Pathway Information
50%
Discrete Markov Random Fields
50%
Microarray Gene Expression
50%
Genomic Research
50%
Biological Pathways
50%
Structure Information
50%
Breast Cancer Recurrence
50%
Field-based Approach
50%
Field-based Model
50%
Procedure Model
50%
Transcriptional Pathways
50%
Gene Set Enrichment Analysis
50%
Computer Science
Subnetwork
100%
markov random field model
100%
Model for Network
100%
False Discovery
20%
Simulation Study
20%
Genomic Research
20%
Biological Pathway
20%
Biochemistry, Genetics and Molecular Biology
Biological Phenomena and Functions Concerning the Entire Organism
100%
DNA Microarray
50%
Gene Set Enrichment Analysis
50%
Mathematics
Markov Random Fields
100%
Test Statistic
25%
False Discovery Rate
25%
Simulation Study
25%