Identifying regulatory targets of cell cycle transcription factors using gene expression and ChIP-chip data
2007
Identifying Regulatory Targets of Cell Cycle Transcription Factors
Sample size: 9
publication
Evidence: high
Author Information
Author(s): Wu Wei-Sheng, Li Wen-Hsiung, Chen Bor-Sen
Primary Institution: National Tsing Hua University
Hypothesis
The genes in B+R+ are more likely to be the regulatory targets of a TF than are the genes in B+R-.
Conclusion
The TRIA algorithm effectively identifies plausible regulatory targets of transcription factors from their binding targets.
Supporting Evidence
- TRIA identified many plausible regulatory targets of cell cycle transcription factors.
- TRIA performed better than two existing methods (MA-Network and MFA).
- The algorithm can identify subsets of highly co-expressed genes among regulatory targets.
Takeaway
The study created a new method to find which genes are controlled by specific proteins in yeast, helping us understand how cells respond to changes.
Methodology
The study developed the Temporal Relationship Identification Algorithm (TRIA) to analyze gene expression and ChIP-chip data.
Statistical Information
P-Value
0.001
Statistical Significance
p<0.001
Digital Object Identifier (DOI)
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