MicroRNA Target Detection and Analysis for Genes Related to Breast Cancer Using MDLcompress
2007
MicroRNA Target Detection and Analysis for Breast Cancer
Sample size: 144
publication
Evidence: moderate
Author Information
Author(s): Evans Scott C, Kourtidis Antonis, Markham T Stephen, Miller Jonathan, Conklin Douglas S, Torres Andrew S
Primary Institution: GE Global Research
Hypothesis
The study explores the relationship between miRNAs, SNPs, and breast cancer using a new algorithm called MDLcompress.
Conclusion
The MDLcompress algorithm identified novel motifs and potential miRNA binding sites in breast cancer-related genes.
Supporting Evidence
- The MDLcompress algorithm outperformed other grammar-based coding methods.
- It identified biologically significant phrases without restrictive priors.
- The tool allows prediction of SNP impact on biological activity.
- MDLcompress improved execution time and specificity of motif detection.
Takeaway
The researchers created a new tool to find important parts of genes related to breast cancer, which could help in future experiments.
Methodology
The study utilized the MDLcompress algorithm for miRNA sequence analysis and motif detection.
Digital Object Identifier (DOI)
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