Extracting transcription factor binding sites from unaligned gene sequences with statistical models
2008

Finding Transcription Factor Binding Sites in Yeast DNA

Sample size: 65 publication Evidence: high

Author Information

Author(s): Lu Chung-Chin, Yuan Wei-Hao, Chen Te-Ming

Primary Institution: National Tsing Hua University

Hypothesis

Can a computational method accurately identify transcription factor binding sites from unaligned DNA sequences?

Conclusion

The study presents a new algorithm that effectively extracts transcription factor binding sites from unaligned gene sequences, outperforming existing methods.

Supporting Evidence

  • The algorithm outperformed MDscan and Cosmo in identifying transcription factor binding sites.
  • The predicted motifs were more consistent with known specificities reported in the literature.
  • The method effectively reduced false positives in motif discovery.

Takeaway

The researchers created a computer program to find important spots in DNA where proteins attach, and it works better than older methods.

Methodology

The study used a binomial probability model and dependency graphs to identify binding motifs from ChIP-chip array data.

Limitations

The algorithm may not perform well for long binding sites (more than 12 base pairs).

Statistical Information

P-Value

<0.001

Statistical Significance

p<0.001

Digital Object Identifier (DOI)

10.1186/1471-2105-9-S12-S7

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