Identifying Motif Modules in the Human Genome
Author Information
Author(s): Cai Xiaohui, Hou Lin, Su Naifang, Hu Haiyan, Deng Minghua, Li Xiaoman
Primary Institution: University of California, San Diego
Hypothesis
Can a computational method systematically identify motif modules in the entire non-coding regions of the human genome?
Conclusion
The study successfully predicted over three million motif modules in the human genome, significantly aiding the understanding of gene regulation.
Supporting Evidence
- The method predicted 3,161,839 motif modules, with 90.8% supported by functional evidence.
- Compared to 14 ChIP-seq experiments, the method predicted 69.6% of the peaks with TFBSs.
- The study identified significant order and distance preferences among motifs in the predicted modules.
Takeaway
The researchers created a computer program that finds patterns in DNA that help control how genes work, which is important for understanding how genes are regulated.
Methodology
The study used a computational method based on discontiguous sequence similarity to identify motif modules in non-coding regions around human genes.
Limitations
The method may miss some CRMs due to genome rearrangements and the limitations of multiple genome alignments.
Statistical Information
P-Value
7.17E-12
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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