Related Experiment Videos
PROSPECT improves cis-acting regulatory element prediction by integrating expression profile data with consensus
W Fujibuchi1, J S Anderson, D Landsman
1Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 45 Center Drive, Bethesda, MD 20894, USA.
Nucleic Acids Research
|September 28, 2001
Summary
This study introduces a new method to reduce false positives in identifying gene regulatory sequences by integrating gene expression data. The developed tool, PROSPECT, improves the accuracy of predicting transcriptional regulatory elements.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Predicting cis-acting transcriptional regulatory sequences using consensus patterns often yields numerous false positives.
- Existing methods lack sufficient specificity in identifying functional regulatory elements.
Purpose of the Study:
- To decrease false positives in the prediction of transcriptional regulatory sequences.
- To integrate gene expression profile data into existing consensus pattern-based search methods.
Main Methods:
- Systematic analysis of expression phenotypes for over 6000 yeast genes across 121 experiments.
- Correlation of gene expression phenotypes with the distribution of 14 known regulatory elements in upstream sequences.
- Development of a metric termed probabilistic element assessment (PEA) for ranking potential regulatory sites.
Main Results:
- The probabilistic element assessment (PEA) method demonstrated significantly higher selectivity compared to naive consensus pattern searches for eight out of 14 regulatory elements.
- Integration of expression profile data effectively reduced false positives in predicting regulatory sequences.
- A web-based tool, PROSPECT, was developed to facilitate searching gene clusters from microarray data.
Conclusions:
- Incorporating gene expression data into sequence analysis is a powerful strategy for improving the accuracy of predicting transcriptional regulatory elements.
- The PROSPECT tool offers a valuable resource for researchers studying gene regulation in yeast.
- This approach enhances the reliability of identifying cis-acting regulatory sequences, advancing genomic research.