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Match is a weight matrix-based tool for searching putative transcription factor binding sites in DNA sequences. Match is closely interconnected and distributed together with the TRANSFAC database. In particular, Match uses the matrix library collected in TRANSFAC and therefore provides the possibility to search for a great variety of different transcription factor binding sites. Several sets of optimised matrix cut-off values are built in the system to provide a variety of search modes of different stringency. The user may construct and save his/her specific user profiles which are selected subsets of matrices including default or user-defined cut-off values. Furthermore a number of tissue-specific profiles are provided that were compiled by the TRANSFAC team. A public version of the Match tool is available at: http://www.gene-regulation.com/pub/programs.html#match. The same program with a different web interface can be found at http://compel.bionet.nsc.ru/Match/Match.html. An advanced version of the tool called Match Professional is available at http://www.biobase.de.

A new method was developed for revealing of composite clusters of cis-elements in promoters of eukaryotic genes that are functionally related or coexpressed. A software system "ClusterScan" have been created that enables: (i) to train system on representative samples of promoters to reveal cis-elements that tend to cluster, (ii) to train system on a number of samples of functionally related promoters to identify functionally coupled transcription factors; (iii) to provide tools for searching of this clusters in genomic sequences to identify and functionally characterize regulatory regions in genome. A number of training samples of different functional and structural groups of promoters were analysed. Search for composite clusters in human chromosomes 21 and 22 reveals a number of interesting examples. Finally, a decision tree system was constructed to classify promoters of several functionally related gene groups. The decision tree system enables to identify new promoters and computationally predict their possible function.

The processes that take place during development and differentiation are directed through coordinated regulation of expression of a large number of genes. One such gene regulatory network provides cell cycle control in eukaryotic organisms. In this work, we have studied the structural features of the 5' regulatory regions of cell cycle-related genes. We developed a new method for identifying composite substructures (modules) in regulatory regions of genes consisting of a binding site for a key transcription factor and additional contextual motifs: potential targets for other transcription factors that may synergistically regulate gene transcription. Applying this method to cell cycle-related promoters, we created a program for context-specific identification of binding sites for transcription factors of the E2F family which are key regulators of the cell cycle. We found that E2F composite modules are found at a high frequency and in close proximity to the start of transcription in cell cycle-related promoters in comparison with other promoters. Using this information, we then searched for E2F sites in genomic sequences with the goal of identifying new genes which play important roles in controlling cell proliferation, differentiation and apoptosis. Using a chromatin immunoprecipitation assay, we then experimentally verified the binding of E2F in vivo to the promoters predicted by the computer-assisted methods. Our identification of new E2F target genes provides new insight into gene regulatory networks and provides a framework for continued analysis of the role of contextual promoter features in transcriptional regulation. The tools described are available at http://compel.bionet.nsc.ru/FunSite/SiteScan.html.