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The MAPPER2 Database: a multi-genome catalog of putative transcription factor binding sites
1Department of Molecular Genetics and Microbiology, University of Florida Genetics Institute, University of Florida, Gainesville, FL 32610, USA. ariva@ufl.edu
Nucleic Acids Research
|November 29, 2011
Summary
The mapper(2) Database provides predicted transcription factor binding sites for human, mouse, and Drosophila genes. This resource aids in analyzing gene regulation across multiple species.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Transcription factors (TFs) play a crucial role in gene regulation by binding to specific DNA sequences.
- Identifying TF binding sites (TFBS) across multiple genomes is essential for understanding conserved regulatory mechanisms.
- Existing databases may lack comprehensive predictions or cross-species comparisons.
Purpose of the Study:
- To introduce the mapper(2) Database, a resource for analyzing TF binding sites in multiple genomes.
- To detail the database's current contents, including predicted binding sites and the underlying probabilistic models.
- To describe the user interface and ongoing development for enhanced functionality.
Main Methods:
- Utilized 1017 probabilistic models derived from over 600 different transcription factors.
- Predicted TFBS in the promoter regions of all human, mouse, and Drosophila genes.
- Developed a web-based system for database access and analysis.
Main Results:
- The mapper(2) Database currently houses predicted TFBS for human, mouse, and Drosophila genomes.
- The database integrates a comprehensive collection of probabilistic models for TF binding.
- A detailed web-based user interface facilitates access and exploration of the predicted binding sites.
Conclusions:
- The mapper(2) Database offers a valuable resource for researchers studying gene regulation and TF binding.
- Ongoing efforts aim to expand the database with experimental data and advanced analytical tools.
- Improvements in the underlying hardware and software platform enhance the database's performance and scalability.
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