Predicting Human Gene Regulatory Elements
Author Information
Author(s): Kim Seon-Young, Kim YongSung
Primary Institution: Korea Research Institute of Bioscience and Biotechnology
Hypothesis
Can gene expression and promoter analysis data be combined to predict transcriptional regulatory elements of human genes?
Conclusion
The study successfully identified and predicted many transcriptional regulatory elements of human genes using a new computational method.
Supporting Evidence
- The method identified many known transcriptional regulatory elements of genes.
- Z scores of gene sets of TFBSs provided better predictions than mRNA levels of transcription factors.
- The approach successfully detected important TFBSs in a given data set.
Takeaway
The researchers found a way to predict important parts of human genes that control how they work by looking at gene expression data and promoter information.
Methodology
The study combined gene expression data analysis with promoter analysis to infer transcriptional regulatory elements.
Limitations
The analysis was restricted to a 1200 bp region around the transcription start site, which may miss regulatory elements located further away.
Statistical Information
P-Value
0
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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