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Published on: November 12, 2012
A computational approach to measuring coherence of gene expression in pathways
Howard H Yang1, Ying Hu, Kenneth H Buetow
1Laboratory of Population Genetics, National Cancer Institute, 41 Library Drive, Bethesda, MD 20892, USA.
Genomics
|June 19, 2004
Summary
Genes within biological pathways show coordinated gene expression more than random sets. This computational analysis of microarray data supports the hypothesis that pathway genes are coordinately regulated.
Area of Science:
- Bioinformatics
- Systems Biology
- Genomics
Background:
- Genes within biological pathways are often coordinately regulated.
- Understanding gene expression coherence is crucial for deciphering cellular functions.
Purpose of the Study:
- To computationally analyze gene expression coherence within biological pathways.
- To test the hypothesis that genes in the same pathway exhibit coordinated regulation compared to random gene sets.
Main Methods:
- Utilized microarray data and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.
- Calculated a coherence indicator based on statistically significant correlations between gene pairs within pathways.
- Compared pathway coherence to that of random gene sets.
Main Results:
- Pathways demonstrated significantly higher coherence indicators than random gene sets, supporting the hypothesis.
- Identified statistically significant pathways across three microarray datasets in both normal and tumor tissues.
- Observed an increase in significant pathways in tumor tissue, potentially linked to higher metabolic rates.
Conclusions:
- Genes within biological pathways are indeed coordinately regulated.
- Essential pathways like those for energy and macromolecule synthesis are consistently coherent across normal and tumor tissues.
- This approach provides a robust method for identifying functionally relevant gene sets.
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