Abstract
Identification of deregulated biomolecular pathways in cancer may be more important than identifi cation of individual genes through differential expression. We have analysed data from 87 microarray datasets, spanning 25 different types of cancer, and have identifi ed several hundred pathways that are statistically signifi cant (p < 0.01) and deregulated in cancer. We also conducted a meta-analysis of 18 mouse cancer datasets and found that a statistically signifi cant number of ontology terms are common between human and mouse cancers and known for their role in carcinogenesis. These point to critical pathways that are disrupted in both human and mouse cancers.
| Original language | English |
|---|---|
| Pages (from-to) | 349-365 |
| Number of pages | 17 |
| Journal | International Journal of Data Mining and Bioinformatics |
| Volume | 8 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2013 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Cancer
- Gene expression
- Hotspots
- Meta analysis
- Microarray
- Pathways
ASJC Scopus subject areas
- Information Systems
- General Biochemistry,Genetics and Molecular Biology
- Library and Information Sciences
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