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The development of chromatin immunoprecipitation sequencing (ChIP-seq) technology has revolutionized the genetic analysis of the basic mechanisms underlying transcription regulation and led to accumulation of information about a huge amount of DNA sequences. There are a lot of web services which are currently available for de novo motif discovery in datasets containing information about DNA/protein binding. An enormous motif diversity makes their finding challenging. In order to avoid the difficulties, researchers use different stochastic approaches. Unfortunately, the efficiency of the motif discovery programs dramatically declines with the query set size increase. This leads to the fact that only a fraction of top 'peak' ChIP-Seq segments can be analyzed or the area of analysis should be narrowed. Thus, the motif discovery in massive datasets remains a challenging issue. Argo_Compute Unified Device Architecture (CUDA) web service is designed to process the massive DNA data. It is a program for the detection of degenerate oligonucleotide motifs of fixed length written in 15-letter IUPAC code. Argo_CUDA is a full-exhaustive approach based on the high-performance GPU technologies. Compared with the existing motif discovery web services, Argo_CUDA shows good prediction quality on simulated sets. The analysis of ChIP-Seq sequences revealed the motifs which correspond to known transcription factor binding sites. [ABSTRACT FROM AUTHOR]

This paper presents implementation of Data Mining and Knowledge Discovery techniques for search-ing for regularities in tables of context features of DNA sequences involved in regulation of transcription. The goal is to discover regularities that relate nucleotide sequences to the functional classes of these sequences. The search patterns for regularities have been constructed in the first-order logic augmented by probabilistic estimates. To this aim, the PC software system “Gene Discovery” has been designed. This system accepts molecular-genetical data retrieved from a database by using SQL queries. Nucleotide sequences of promoters of several functional systems were extracted from the TRRD database (http://wwwmgs.bionet.nsc.ru/mgs/gnw/trrd/) and analysed. The data in-clude nucleotide sequences of erythroid-specific gene promoters, endocrine system gene promoters, promoter regions of the genes controlling cell cycle, promoter of genes regulating lipid metabolism, and muscle-specific gene promoters. Several regularities that relate the nucleotide sequences in the regulatory DNA and their location relative to the transcription start with each functional class have been found. [ABSTRACT FROM AUTHOR]

A method is proposed to automatically search for patterns in the mutual location of context signals in regulatory DNA sequences. The procedure is based on the methods of Data Mining and Knowledge Discovery software, implemented in a computer system Gene Discovery. This system was used to study erythroid-specific promoters and promoters of the endocrine-system genes from TRRD. We detected some trends in occurrence and localization of specific oligonucleotide groups. [ABSTRACT FROM AUTHOR]

Computer system mRNA-FAST (mRNA Function, Activity, STructure; http://wwwmgs.bionet.nsc.ru/mgs/dbases/trsig/) is described. The system has been developed to analyze nucleotide sequences of mRNA and to measure their essential properties. The system compiles the data base on translation signals including nucleotide sequences of the regulatory regions with structural and experimental information on their specific activities. It also contains programs to search for local homology between mRNA and translation signals, to search for potential signals basing on analysis of the oligonucleotide dictionaries, and to model secondary RNA structure. Possible applications of the system mRNA-FAST are discussed. [ABSTRACT FROM AUTHOR]