Binding sites for proteins in the genome have a great regulatory impact on the gene activities in their neighborhood. Since these interactions are highly dynamic with regard to the cell’s status, we have experimental knowledge about the actual occupancy of these sites only for a very small percentage of them. Predictive tools are thus essential for deciphering the full regulatory potential of gene control regions like promoters, enhancers, etc.
these matrices can be individually selected and combined to “profiles”; a number of pre-defined profiles are available for subsequent sequence analysis. Matrix matches are visualized along the gene sequences in a customizable manner.
Visualization of transcription factor binding sites (TFBSs) with geneXplain platform’s genome browser. Click image for an enlarged view.
The built-in genome browser enables to comfortably zoom-out to chromosomal level, or to zoom-in to the nucleotide level. Individual sites are clickable to invoke detailed information.
Therefore, the geneXplain platform provides an empirical way to identify the specific combination of sites that characterizes a given set of co-regulating promoters.
Complex promoter analysis, visualization of transcription factor binding sites (TFBSs) constituting a “promoter model”. (Click Image for an enlarged view.)
These specific combinations, also called “promoter models”, can be further used for screening genomic sequences or promoter databases. A comprehensive collection of mammalian promoters comes along with the TRANSFAC® database in its TRANSPRO section. The density of model matches is visualized by graded shading.
Promoter analysis for matches with a model comprising a set of transcription factor binding sites (TFBSs). (Click Image for an enlarged view.)
Deyneko, I. V., Kel, A. E., Kel-Margoulis, O. V., Deineko, E. V., Wingender, E. and Weiss, S. (2013) MatrixCatch – a novel tool for the recognition of composite regulatory elements in promoters. BMC Bioinformatics
Stegmaier, P., Kel, A., Wingender, E., Borlak, J. (2013) A discriminative approach for unsupervised clustering of DNA sequence motifs. PLoS Comput. Biol.
Stegmaier P., Voss N., Meier T., Kel A., Wingender E., Borlak J. (2011) Advanced computational biology methods identify molecular switches for malignancy in an EGF mouse model of liver cancer. PLoS ONE
Wingender E. (2008) The TRANSFAC project as an example of framework technology that supports the analysis of genomic regulation. Brief Bioinform.
Kel A., Konovalova T., Waleev T., Cheremushkin E., Kel-Margoulis O., Wingender, E. (2006) Composite Module Analyst: a fitness-based tool for identification of transcription factor binding site combinations. Bioinformatics
Waleev T. Shtokalo D., Konovalova T., Voss N., Cheremushkin E., Stegmaier P., Kel-Margoulis O., Wingender E., Kel A. (2006) Composite Module Analyst: identification of transcription factor binding site combinations using genetic algorithm. Nucleic Acids Res.
Kel A.E., Gössling E., Reuter I., Cheremushkin E., Kel-Margoulis O.V., Wingender E. (2003) MATCH: A tool for searching transcription factor binding sites in DNA sequences. Nucleic Acids Res.
Get the most comprehensive overview about potential regulatory elements in your sequences.
Fast and immediate analysis with a small library of positional weight matrices.
Make use of the full potential of the gold standard in the field, the TRANSFAC® database.
Automatically generate complex promoter models.
Generate high-quality hypotheses about the transcription factors acting on a given set of co-regulated promoters.
Search for additional genes fitting to your promoter model.
