Electrogenerated chemiluminescence of BODIPY, Ru(bpy)3(2+), and 9,10-diphenylanthracene using interdigitated array electrodes.

Interdigitated array electrodes (IDAs) were used to produce steady-state electrogenerated chemiluminescence (ECL) by annihilation of oxidized and reduced forms of a substituted boron dipyrromethene (BODIPY) dye, 9,10-diphenylanthracene (DPA), and ruthenium(II) tris(bypiridine) (Ru(bpy)3(2+)). Digital simulations were in good agreement with the experimentally obtained currents and light outputs. Coreactant experiments, using tri-n-propylamine and benzoyl peroxide as a sacrificial homogeneous reductant or oxidant, show currents corresponding to electrode reactions of the dyes and not the oxidation or reduction of the coreactants. The results show that interdigitated arrays can produce stable ECL where the light intensity is magnified due to the larger currents as a consequence of feedback between generator and collector electrodes in the IDA. The light output for ECL is around 100 times higher than that obtained with regular planar electrodes with similar area.

Snipping polymorphisms from large EST collections in barley (Hordeum vulgare L.).

The public EST (expressed sequence tag) databases represent an enormous but heterogeneous repository of sequences, including many from a broad selection of plant species and a wide range of distinct varieties. The significant redundancy within large EST collections makes them an attractive resource for rapid pre-selection of candidate sequence polymorphisms. Here we present a strategy that allows rapid identification of candidate SNPs in barley (Hordeum vulgare L.) using publicly available EST databases. Analysis of 271,630 EST sequences from different cDNA libraries, representing 23 different barley varieties, resulted in the generation of 56,302 tentative consensus sequences. In all, 8171 of these unigene sequences are members of clusters with six or more ESTs. By applying a novel SNP detection algorithm (SNiPpER) to these sequences, we identified 3069 candidate inter-varietal SNPs. In order to verify these candidate SNPs, we selected a small subset of 63 present in 36 ESTs. Of the 63 SNPs selected, we were able to validate 54 (86%) using a direct sequencing approach. For further verification, 28 ESTs were mapped to distinct loci within the barley genome. The polymorphism information content (PIC) and nucleotide diversity (pi) values of the SNPs identified by the SNiPpER algorithm are significantly higher than those that were obtained by random sequencing. This demonstrates the efficiency of our strategy for SNP identification and the cost-efficient development of EST-based SNP-markers.

SNAPping up functionally related genes based on context information: a colinearity-free approach.

We describe a computational approach for finding genes that are functionally related but do not possess any noticeable sequence similarity. Our method, which we call SNAP (similarity-neighborhood approach), reveals the conservation of gene order on bacterial chromosomes based on both cross-genome comparison and context information. The novel feature of this method is that it does not rely on detection of conserved colinear gene strings. Instead, we introduce the notion of a similarity-neighborhood graph (SN-graph), which is constructed from the chains of similarity and neighborhood relationships between orthologous genes in different genomes and adjacent genes in the same genome, respectively. An SN-cycle is defined as a closed path on the SN-graph and is postulated to preferentially join functionally related gene products that participate in the same biochemical or regulatory process. We demonstrate the substantial non-randomness and functional significance of SN-cycles derived from real genome data and estimate the prediction accuracy of SNAP in assigning broad function to uncharacterized proteins. Examples of practical application of SNAP for improving the quality of genome annotation are described.

[Automatic generation of gene network schemes based on their formalized description in the GeneNet database]. / Avtomaticheskaia generatsiia skhem gennykh setei na osnove ikh formalizovannogo opisaniia v baze dannykh GeneNet.

A database for gene networks GeneNet was created. The main principles of formalized description of gene networks for the cases of regulation of antiviral responses and hemopoiesis were developed. A program for automatic graphical representation of diagrams of gene networks was created, which is based on their formalized description. A system of filters was developed, which makes it possible to select individual network components for graphical representation. The selection can be performed with respect to specific type of treatment, species, and/or cell type. The GeneNet database is accessible via Internet at http://wwwmgs.bionet.nsc.ru/systems/MGL/Gen eNet.

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.

GeneNet: a gene network database and its automated visualization.

MOTIVATION: Gene networks that provide the regulation of physiological processes are the basic feature of organisms. Information regarding the regulation of gene expression and signal transduction pathways is increasing rapidly. However, the information is hard to formalize and systematize. Ways and means for automated visualization of the gene networks based on their formalized description are needed. RESULTS: The object-oriented database GeneNet and the software for its automated visualization have been developed. The main principles of a formalized description of the gene network have been worked out. Antiviral response and erythropoiesis are provided as examples to show how this is achieved. The GeneNet graphical user interface written in Java provides automated generation of the gene network diagrams and allows visualization and exploration of the GeneNet database through the Internet. A system of filters allows the selection of particular components of the network for visualization. AVAILABILITY: The GeneNet database and its graphical user interface are available at http://wwwmgs.bionet.nsc.ru/systems/MGL/GeneN et/ CONTACT: fedor@bionet.nsc.ru