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An associative analysis of gene expression array data
Igor Dozmorov, Michael Centola
Immunology - Wakeland Lab
Immunology
Research output
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Contribution to journal
›
Article
›
peer-review
102
Scopus citations
Overview
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Dive into the research topics of 'An associative analysis of gene expression array data'. Together they form a unique fingerprint.
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Mathematics
Gene Expression
100%
Gene
77%
Microarray
33%
Mouse
33%
Large Data Sets
32%
Specificity
31%
Experiment
29%
Standards
21%
CDNA
21%
Messenger RNA
18%
False Positive
17%
Comparative Analysis
15%
t-test
15%
Significance level
15%
Trade-offs
13%
Regression Analysis
13%
Normalization
13%
Statistical Analysis
12%
Family
12%
Background
11%
Classify
10%
Interpretation
9%
Engineering & Materials Science
Gene expression
87%
Genes
75%
Microarrays
30%
Messenger RNA
18%
Experiments
14%
Regression analysis
13%
Statistical methods
11%
Medicine & Life Sciences
Gene Expression
47%
Genes
27%
Datasets
27%
Sensitivity and Specificity
16%
Oligonucleotide Array Sequence Analysis
11%
Regression Analysis
7%
Messenger RNA
6%
Control Groups
6%
Chemical Compounds
Microarrays
86%
Complementary DNA
41%