Tatyana I. Merkulova

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rSNP_Guide is a novel curated database system for analysis of transcription factor (TF) binding to target sequences in regulatory gene regions altered by mutations. It accumulates experimental data on naturally occurring site variants in regulatory gene regions and site-directed mutations. This database system also contains the web tools for SNP analysis,(More)
The GR-TRRD section of the TRRD database contains the presently largest sample of published nucleotide sequences with experimentally confirmed binding to the glucocorticoid hormone receptor (GR). This sample comprises 160 glucocorticoid receptor binding sites (GRbs) from 77 vertebrate glucocorticoid-regulated genes. Analysis of this sample has demonstrated(More)
Transcription Regulatory Regions Database (TRRD) is an informational resource containing an integrated description of the gene transcription regulation. An entry of the database corresponds to a gene and contains the data on localization and functions of the transcription regulatory regions as well as gene expression patterns. TRRD contains only(More)
The transcription factor GAGA, encoded by the gene Trl, controls expression of many Drosophila melanogaster genes. We have compiled the presently largest sample (120 sites) of published nucleotide sequences with experimentally confirmed binding to GAGA protein. Analysis of the sample has demonstrated that despite an apparent structural diversity of the GAGA(More)
Gel shift assays were used to study the formation of transcription factors of the AP-1 family in the CNS of Helix during the acquisition of a conditioned defensive reflex based on food aversion. Increases in the DNA-binding activity of AP-1 factors were seen 1-3 h after training. Modeling of "learning" in an in situ system (incubation of the CNS in the(More)
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(More)
BACKGROUND Reliable transcription factor binding site (TFBS) prediction methods are essential for computer annotation of large amount of genome sequence data. However, current methods to predict TFBSs are hampered by the high false-positive rates that occur when only sequence conservation at the core binding-sites is considered. RESULTS To improve this(More)
The recognition of transcription factor binding sites (TFBSs) is the first step on the way to deciphering the DNA regulatory code. There is a large variety of experimental approaches providing information on TFBS location in genomic sequences. Many computational approaches to TFBS recognition based on the experimental data obtained are available, each(More)
A vast amount of SNPs derived from genome-wide association studies are represented by non-coding ones, therefore exacerbating the need for effective identification of regulatory SNPs (rSNPs) among them. However, this task remains challenging since the regulatory part of the human genome is annotated much poorly as opposed to coding regions. Here we describe(More)