Biomedical subjects

A E Kel

Publications and source records attributed to A E Kel.

At least 19 recordsLinked to original sources

PubMed2006

TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes.

The TRANSFAC database on transcription factors, their binding sites, nucleotide distribution matrices and regulated genes as well as the complementing database TRANSCompel on composite elements have been further enhanced on various levels. A new web interface with different search options and integrated versions of Match and Patch provides increased functionality for TRANSFAC. The list of databases which are linked to the common GENE table of TRANSFAC and TRANSCompel has been extended by: Ensembl, UniGene, EntrezGene, HumanPSD and TRANSPRO. Standard gene names from HGNC, MGI and RGD, are included for human, mouse and rat genes, respectively. With the help of InterProScan, Pfam, SMART and PROSITE domains are assigned automatically to the protein sequences of the transcription factors. TRANSCompel contains now, in addition to the COMPEL table, a separate table for detailed information on the experimental EVIDENCE on which the composite elements are based. Finally, for TRANSFAC, in respect of data growth, in particular the gain of Drosophila transcription factor binding sites (by courtesy of the Drosophila DNase I footprint database) and of Arabidopsis factors (by courtesy of DATF, Database of Arabidopsis Transcription Factors) has to be stressed. The here described public releases, TRANSFAC 7.0 and TRANSCompel 7.0, are accessible under http://www.gene-regulation.com/pub/databases.html.

Animals↗

PubMed2005

P-Match: transcription factor binding site search by combining patterns and weight matrices.

P-Match is a new tool for identifying transcription factor (TF) binding sites in DNA sequences. It combines pattern matching and weight matrix approaches thus providing higher accuracy of recognition than each of the methods alone. P-Match is closely interconnected with the TRANSFAC database. In particular, P-Match uses the matrix library as well as sets of aligned known TF-binding sites collected in TRANSFAC and therefore provides the possibility to search for a large variety of different TF binding sites. Using results of extensive tests of recognition accuracy, we selected three sets of optimized cut-off values that minimize either false negatives or false positives, or the sum of both errors. Comparison with the weight matrix approaches such as Matchtrade mark tool shows that P-Match generally provides superior recognition accuracy in the area of low false negative errors (high sensitivity). As familiar to the user of Matchtrade mark, P-Match also allows to save user-specific profiles that include selected subsets of matrices with corresponding TF-binding sites 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 P-Match tool is available at http://www.gene-regulation.com/cgi-bin/pub/programs/pmatch/bin/p-match.cgi.

Algorithms↗

PubMed2003

MATCH: A tool for searching transcription factor binding sites in DNA sequences.

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.

Algorithms↗

PubMed2003

TRANSFAC: transcriptional regulation, from patterns to profiles.

The TRANSFAC database on eukaryotic transcriptional regulation, comprising data on transcription factors, their target genes and regulatory binding sites, has been extended and further developed, both in number of entries and in the scope and structure of the collected data. Structured fields for expression patterns have been introduced for transcription factors from human and mouse, using the CYTOMER database on anatomical structures and developmental stages. The functionality of Match, a tool for matrix-based search of transcription factor binding sites, has been enhanced. For instance, the program now comes along with a number of tissue-(or state-)specific profiles and new profiles can be created and modified with Match Profiler. The GENE table was extended and gained in importance, containing amongst others links to LocusLink, RefSeq and OMIM now. Further, (direct) links between factor and target gene on one hand and between gene and encoded factor on the other hand were introduced. The TRANSFAC public release is available at http://www.gene-regulation.com. For yeast an additional release including the latest data was made available separately as TRANSFAC Saccharomyces Module (TSM) at http://transfac.gbf.de. For CYTOMER free download versions are available at http://www.biobase.de:8080/index.html.

Animals↗

PubMed2002

Automatic annotation of genomic regulatory sequences by searching for composite clusters.

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.

Animals↗

PubMed2001

Computer-assisted identification of cell cycle-related genes: new targets for E2F transcription factors.

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.

Animals↗

PubMed2000

Transcription regulatory regions database (TRRD): its status in 2000.

Transcription Regulatory Regions Database (TRRD) has been developed for accumulation of experimental information on the structure-function features of regulatory regions of eukaryotic genes. Each entry in TRRD corresponds to a particular gene and contains a description of structure-function features of its regulatory regions (transcription factor binding sites, promoters, enhancers, silencers, etc.) and gene expression regulation patterns. The current release, TRRD 4.2.5, comprises the description of 760 genes, 3403 expression patterns, and >4600 regulatory elements including 3604 transcription factor binding sites, 600 promoters and 152 enhancers. This information was obtained through annotation of 2537 scientific publications. TRRD 4.2.5 is available through the WWW at http://wwwmgs.bionet.nsc.ru/mgs/dbases/trrd4/

Databases, Factual↗

PubMed2000

COMPEL: a database on composite regulatory elements providing combinatorial transcriptional regulation.

COMPEL is a database on composite regulatory elements, the basic structures of combinatorial regulation. Composite regulatory elements contain two closely situated binding sites for distinct transcription factors and represent minimal functional units providing combinatorial transcriptional regulation. Both specific factor-DNA and factor-factor interactions contribute to the function of composite elements (CEs). Information about the structure of known CEs and specific gene regulation achieved through such CEs appears to be extremely useful for promoter prediction, for gene function prediction and for applied gene engineering as well. The structure of the relational model of COMPEL is determined by the concept of molecular structure and regulatory role of CEs. Based on the set of a particular CE, a program has been developed for searching potential CEs in gene regulatory regions. WWW search and browse routines were developed for COMPEL release 3.0. The COMPEL database equipped with the search and browse tools is available at http://compel.bionet.nsc.ru/. The program for prediction of potential CEs of NFAT type is available at http://compel.bionet.nsc. ru/FunSite.html and http://transfac.gbf.de/dbsearch/funsitep/ s_comp.html

Database Management Systems↗

PubMed1999

Transcription Regulatory Regions Database (TRRD):its status in 1999.

The Transcription Regulatory Regions Database (TRRD) is a curated database designed for accumulation of experimental data on extended regulatory regions of eukaryotic genes, the regulatory elements they contain, i.e., transcription factor binding sites, promoters, enhancers, silencers, etc., and expression patterns of the genes. Release 4.1 of TRRD offers a number of significant improvements, in particular, a more detailed description of transcription factor binding sites, transcription factors per se, and gene expression patterns in a computer-readable format. In addition, the new TRRD release provides considerably more references to other molecular biological databases. TRRD 4.1 is installed under SRS and is available through the WWW at http://www.bionet.nsc.ru/trrd/

Animals↗

PubMed1999

Expanding the TRANSFAC database towards an expert system of regulatory molecular mechanisms.

TRANSFAC is a database on transcription factors, their genomic binding sites and DNA-binding profiles. In addition to being updated and extended by new features, it has been complemented now by a series of additional database modules. Among them, modules which provide data about signal transduction pathways (TRANSPATH) or about cell types/organs/developmental stages (CYTOMER) are available as well as an updated version of the previously described COMPEL database. The databases are available on the WWW at http://transfac.gbf.de/

Animals↗

PubMed1998

Eukaryotic mRNAs encoding abundant and scarce proteins are statistically dissimilar in many structural features.

It is well known that non-coding mRNA sequences are dissimilar in many structural features. For individual mRNAs correlations were found for some of these features and their translational efficiency. However, no systematic statistical analysis was undertaken to relate protein abundance and structural characteristics of mRNA encoding the given protein. We have demonstrated that structural and contextual features of eukaryotic mRNAs encoding high- and low-abundant proteins differ in the 5' untranslated regions (UTR). Statistically, 5' UTRs of low-expression mRNAs are longer, their guanine plus cytosine content is higher, they have a less optimal context of the translation initiation codons of the main open reading frames and contain more frequently upstream AUG than 5' UTRs of high-expression mRNAs. Apart from the differences in 5' UTRs, high-expression mRNAs contain stronger termination signals. Structural features of low- and high-expression mRNAs are likely to contribute to the yield of their protein products.

5' Untranslated Regions↗

PubMed1998

Databases on transcriptional regulation: TRANSFAC, TRRD and COMPEL.

TRANSFAC, TRRD (Transcription Regulatory Region Database) and COMPEL are databases which store information about transcriptional regulation in eukaryotic cells. The three databases provide distinct views on the components involved in transcription: transcription factors and their binding sites and binding profiles (TRANSFAC), the regulatory hierarchy of whole genes (TRRD), and the structural and functional properties of composite elements (COMPEL). The quantitative and qualitative changes of all three databases and connected programs are described. The databases are accessible via WWW:http://transfac.gbf.de/TRANSFAC orhttp://www.bionet.nsc.ru/TRRD

Animals↗

PubMed1998

GeneExpress: a computer system for description, analysis, and recognition of regulatory sequences in eukaryotic genome.

GeneExpress system has been designed to integrate description, analysis, and recognition of eukaryotic regulatory sequences. The system includes 5 basic units: (1) GeneNet contains an object-oriented database for accumulation of data on gene networks and signal transduction pathways and a Java-based viewer that allows an exploration and visualization of the GeneNet information; (2) Transcription Regulation combines the database on transcription regulatory regions of eukaryotic genes (TRRD) and TRRD Viewer; (3) Transcription Factor Binding Site Recognition contains a compilation of transcription factor binding sites (TFBSC) and programs for their analysis and recognition; (4) mRNA Translation is designed for analysis of structural and contextual features of mRNA 5'UTRs and prediction of their translation efficiency; and (5) ACTIVITY is the module for analysis and site activity prediction of a given nucleotide sequence. Integration of the databases in the GeneExpress is based on the Sequence Retrieval System (SRS) created in the European Bioinformatics Institute.

Artificial Intelligence↗

PubMed1997

TRANSFAC, TRRD and COMPEL: towards a federated database system on transcriptional regulation.

Three databases that provide data on transcriptional regulation are described. TRANSFAC is a database on transcription factors and their DNA binding sites. TRRD (Transcription Regulatory Region Database) collects information about complete regulatory regions, their regulation properties and architecture. COMPEL comprises specific information on composite regulatory elements. Here, we describe the present status of these databases and the first steps towards their federation.

Animals↗

PubMed1997

Search for DNA conformational features for functional sites. Investigation of the TATA box.

A method for search of DNA conformational features significant for functional sites is developed. The method uses helical angles averaged for known X-ray structures. Nucleotide sequences are assigned mean angles in a given region. Choice of the significant angles is based on their capabilities to discriminate functional sites from random sequences. The yeast, invertebrate and vertebrate TATA boxes are analyzed using this method. Regions neighboring the TATA boxes are found to have smaller helical twist and roll angles. The results agree with the experimental data on Dickerson-Drew dodecamers. There is a significant decrease in the length of a small roll angle region with increasing complexity of taxon organization.

Animals↗

PubMed1995

A compilation of composite regulatory elements affecting gene transcription in vertebrates.

Over the past years, evidence has been accumulating for a fundamental role of protein-protein interactions between transcription factors in gene-specific transcription regulation. Many of these interactions run within composite elements containing binding sites for several factors. We have selected 101 composite regulatory elements identified experimentally in the regulatory regions of 64 genes of vertebrates and of their viruses and briefly described them in a compilation. Of these, 82 composite elements are of the synergistic type and 19 of the antagonistic type. Within the synergistic type composite elements, transcription factors bind to the corresponding sites simultaneously, thus cooperatively activating transcription. The factors, binding to their target sites within antagonistic type composite elements, produce opposing effects on transcription. The nucleotide sequence and localization in the genes, the names and brief description of transcription factors, are provided for each composite element, including a representation of experimental data on its functioning. Most of the composite elements (3/4) fall between -250 bp and the transcription start site. The distance between the binding sites within the composite elements described varies from complete overlapping to 80 bp. The compilation of composite elements is presented in the database COMPEL which is electronically accessible by anonymous ftp via internet.

Animals↗

PubMed1995

Eukaryotic promoter recognition by binding sites for transcription factors.

A method for identification of eukaryotic promoters by localization of binding sites for transcription factors has been suggested. The binding sites for a range of transcription factors have been found to be distributed unevenly. Based on these distributions, we have constructed a weight matrix of binding site localization. On the basis of the weight matrix we have, in turn, designed an algorithm for promoter recognition. To increase the accuracy of the method, we have developed a routine that breaks any promoter sample into subsamples. The method to be reported on allows much better recognition accuracy than does the approach based on detection of the TATA box. In particular, the overprediction error is three times lower following our method. The program FunSiteP recognizes promoters from newly uncovered sequences and tentatively identifies the functional class the promoters must belong to. We have introduced the notion of 'regulatory potential' for the degree to which any region of the sequences is similar to the real eukaryotic promoter. By making use of the potential, we have revealed putative transcription start sites and extended regions of transcription regulation.

Algorithms↗

PubMed1995

Computer tool FUNSITE for analysis of eukaryotic regulatory genomic sequences.

We present the computer tool FUNSITE for description and analysis of regulatory sequences of eukaryotic genomes. The tool consists of the following main parts: 1) An integrated database for genomic regulatory sequences. The integrated database was designed on the basis of the databases TRANSFAC (Wingender 1994) and TRRD (Kel et al. 1995) that are currently under development. The following functions are performed: i) linkage to the EMBL database; ii) preparing samples of definite types of functional sites with their flanking sequences; iii) preparing samples of promoter sequences; iv) preparing samples of transcription factors classified with regard to structural and functional features of DNA binding and activating domains, functional families of the factors, their tissue specificity and other functional features; v) access to data on mutual disposition of cis-elements within the regulatory regions. 2) The second component of FUNSITE tool is the set of programs for analysis of the structural organization of regulatory sequences: i) Program for revealing of potential transcription factors binding sites based on their consensi; ii) program for revealing of the potential binding sites using homology search with nucleotide sequences of real binding sites; iii) program for analysis of oligonucleotide context features which are characteristic of flank sequences of the binding sites; iv) program for design of recognition method for the functional sites based on generalized weight matrix; v) program for revealing potential composite elements. The results of analysis of the promoter sequences of eukaryotic genes with the FUNSITE are presented, too.

Amino Acid Sequence↗