Finding microRNA regulatory modules in the human genome
Author Information
Author(s): Tran Dang Hung, Satou Kenji, Ho Tu Bao
Primary Institution: Japan Advanced Institute of Science and Technology
Hypothesis
Can a rule-based learning method identify functional modules of microRNAs and their target genes in human cellular processes?
Conclusion
The identified microRNA regulatory modules show high correlation in expression patterns and are associated with various types of human cancer.
Supporting Evidence
- 79 microRNA regulatory modules were identified from human genes and miRNAs.
- The modules consist of highly-related miRNAs and their target genes.
- The expression patterns of miRNAs and mRNAs in the same module are highly correlated.
- Several identified miRNAs are associated with different types of human cancer.
Takeaway
This study found groups of tiny RNA molecules that work together to control gene activity in humans, which could help us understand cancer better.
Methodology
A rule-based learning method was used to analyze miRNA-target binding data and gene expression profiles to identify microRNA regulatory modules.
Potential Biases
The rule induction process may introduce bias if the rules are derived from unrepresentative examples.
Limitations
The method may produce many insignificant rules, and the quality of the identified modules depends on the choice of similarity measure.
Participant Demographics
The study analyzed expression profiles from 89 human cancer samples.
Statistical Information
P-Value
8.63E-03
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website