Computational identification of Transcription Factor Binding Sites

Dr. Riva is one of the developers of MAPPER, an online resource to search for putative TFBSs in DNA sequences. MAPPER combines a large collection of TFBS models (over 1,000 models for about 800 different transcription factors) with a database of precomputed putative TFBSs in the genomes of three different organisms (human, mouse and drosophila), and a tool to scan any arbitrary sequence for predicted binding sites.

We are currently working on developing two new modules that build on the MAPPER platform to provide new analysis features. The first one, rSNP-MAPPER, aims at exploring the relationships between Single-Nucleotide Polymorphisms (SNPs) and TFBSs. It can be used to locate SNPs that affect predicted binding sites, and that can therefore have a regulatory effect.

The second module allows users to build new TFBS models starting from an alignment of known binding sites. The new models can be tested on known binding sites, and are then added to the user's private library of models. They can then be used to analyze individual sequences like the builtin MAPPER models, or for whole-genome scans.

Joint work with V.D. Marinescu, University of Utah.

References

1. Marinescu, V. D., Kohane, I. S., and Riva, A. (2005). MAPPER: a search engine for the computational identification of putative transcription factor binding sites in multiple genomes. BMC Bioinformatics 2005, 6(1):79.
2. Marinescu, V. D., Kohane, I. S., and Riva, A. (2005). The MAPPER database: a multi-genome catalog of putative transcription factor binding sites. Nucleic Acids Res 33 (Database Issue), D91-97.