The YEASTRACT database: an upgraded information system for the analysis of gene and genomic transcription regulation inSaccharomyces cerevisiae
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- TL;DR
- YEASTRACT is an upgraded information system designed to analyze and predict transcription regulatory associations in *Saccharomyces cerevisiae* (yeast).
- Problem
- Not specified in the abstract.
- Method
- The database was updated to include over 200,000 regulatory associations, detailed experimental conditions, and whether transcription factors act as activators or repressors, enabling new query options and ranking tools.
- Results
- Not specified in the abstract.
- Contributions
- The release introduces new query capabilities for environmental conditions, experimental evidence, and regulatory effects, along with tools to rank transcription factors by their relative importance.
- Limitations
- Not specified in the abstract.
- Takeaways
- This updated system provides valuable data and services to support ongoing research by yeast biologists and systems biology researchers.
- Applications
- Analysis and prediction of gene and genomic transcription regulation in yeast for biological research.
- Topics
- Transcription regulation; Biological databases; Systems biology; Yeast genomics
- For industry
- Biotechnology and life sciences.
- Why it matters
- Serves as an essential resource for yeast biologists and systems biology researchers studying transcriptional regulation.
Abstract
The YEASTRACT (http://www.yeastract.com) information system is a tool for the analysis and prediction of transcription regulatory associations in Saccharomyces cerevisiae. Last updated in June 2013, this database contains over 200,000 regulatory associations between transcription factors (TFs) and target genes, including 326 DNA binding sites for 113 TFs. All regulatory associations stored in YEASTRACT were revisited and new information was added on the experimental conditions in which those associations take place and on whether the TF is acting on its target genes as activator or repressor. Based on this information, new queries were developed allowing the selection of specific environmental conditions, experimental evidence or positive/negative regulatory effect. This release further offers tools to rank the TFs controlling a gene or genome-wide response by their relative importance, based on (i) the percentage of target genes in the data set; (ii) the enrichment of the TF regulon in the data set when compared with the genome; or (iii) the score computed using the TFRank system, which selects and prioritizes the relevant TFs by walking through the yeast regulatory network. We expect that with the new data and services made available, the system will continue to be instrumental for yeast biologists and systems biology researchers.