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ChIPXpress: Using publicly available gene expression data to improve ChIP-seq and ChIP-chip target gene ranking
George Wu,
Hongkai Ji
Bloomberg School of Public Health
Research output
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Contribution to journal
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Article
›
peer-review
12
Scopus citations
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Dive into the research topics of 'ChIPXpress: Using publicly available gene expression data to improve ChIP-seq and ChIP-chip target gene ranking'. Together they form a unique fingerprint.
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Mathematics
Transcription Factor
100%
Gene Expression Data
83%
Chip
81%
Ranking
64%
Gene
62%
Target
54%
Experiment
21%
Perturbation
19%
Mouse
8%
Gene Expression
8%
Demonstrate
8%
Genome
7%
Human
6%
Choose
6%
Background
6%
Prediction
5%
Evaluate
5%
Relationships
4%
Engineering & Materials Science
Transcription factors
91%
Gene expression
69%
Genes
60%
Experiments
10%
Binding sites
9%
Genomics
7%
Medicine & Life Sciences
Chromatin Immunoprecipitation Sequencing
82%
Transcription Factors
47%
Gene Expression
38%
Genes
25%
Data Analysis
10%
Research Personnel
9%
Datasets
5%
Binding Sites
5%
Genome
4%
Databases
4%
Chemical Compounds
Heterogeneity
58%
Binding Site
44%
Strength
40%
Amount
27%