Identifying miRNA Targets Using Gene Expression Profiles
Author Information
Author(s): Joung Je-Gun, Fei Zhang
Primary Institution: Boyce Thompson Institute for Plant Research, Cornell University
Hypothesis
Can gene expression profiles help in identifying condition-specific miRNA targets?
Conclusion
The study presents a novel framework for screening target genes by integrating gene expression profiles and sequence information.
Supporting Evidence
- The proposed model yielded a low false positive rate.
- Gene expression profiles can help identify miRNA targets that are missed by sequence analysis.
- The study used a total of 211 conditions for analysis.
Takeaway
This study shows that we can find important genes that miRNAs control by looking at how genes are expressed in different conditions.
Methodology
The study used a support vector machine (SVM) classifier combined with gene expression profiles and miRNA/mRNA sequence information to identify targets.
Potential Biases
Potential bias due to reliance on existing validated datasets and the imbalance in training data.
Limitations
The method relies on the availability of validated target genes and may not perform well without high-quality expression data.
Digital Object Identifier (DOI)
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