GeneExpress: an integrator for databases and computer systems accessible by the Internet and intended for studying eukaryotic gene expression

We have developed GeneExpress that is the WWW-oriented integrator for the databases and systems supporting the investigation of gene expression. The total number of the Web-based resources integrated is 30. The database GeneNet on molecular events forming gene networks was assigned its integrative core. To navigate all these WWW-available resources, the SRS, HTML, and Java viewers were developed, http:@wwwmgs.bionet.nsc.ru/systems/GeneExpress/.     

Generalized Chemokinetic Method for Gene Network Simulation

Development of methods for mathematical simulation of biological systems and building specific simulations is an important trend of bioinformatics. Here we describe the method of generalized chemokinetic simulation generating flexible and adequate simulations of various biological systems. Adequate simulations of complex nonlinear gene networks—control system of cholesterol by synthesis in the cell and erythrocyte differentiation and maturation—are given as examples. The simulations were expressed in terms of unit processes—biochemical reactions. Optimal sets of parameters were determined and the systems were numerically simulated under various conditions. The simulations allow us to study the possible functional conditions of these gene networks, calculate the consequences of mutations, and define optimal strategies for their correction including therapeutic ones. A graphical user interface for these simulations is available at http://wwwmgs.bionet.nsc.ru/systems/MGL/GeneNet/     

A Systems-Genetics Approach and Data Mining Tool to Assist in the Discovery of Genes Underlying Complex Traits in Oryza sativa

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance.     

GeneNet database: description and modeling of gene networks

Almost all cellular processes in an organism are controlled by gene networks. Here we report on the analysis of gene networks functioning using two associated methods - data accumulation in GeneNet system and generalized chemical kinetic method for mathematical simulation of gene network functional dynamics. The technology of the usage of these methods is shown on the example of the gene network of macrophage activation.     

A systems approach to morphogenesis in Arabidopsis thaliana: I. AGNS database

In systems biology, study of a complex and multicomponent system, such as morphogenesis, comprises accumulation of data on morphogenetic processes in databases, classification and logical analysis of this information, and computer simulation of the processes in question using the data accumulated and the results of their analysis. This paper describes realization of the first steps in a systems study of morphogenesis (annotating research papers, compiling information in a database, data systematization, and their logical analysis) by the example of Arabidopsis thaliana, a model object in plant molecular biology. The database AGNS (Arabidopsis GeneNet Supplementary; http://wwwmgs.bionet.nsc.ru/agns) contains the experimentally confirmed information from published papers on specific features of gene expression and phenotypes of wild-type, mutant, and transgenic A. thaliana plants. AGNS queries and logical data analysis with the aid of specially developed software makes it possible to model various morphogenetic processes from gene expression to functioning of gene networks and their contribution to the development of certain traits.

     

KEGG: Kyoto Encyclopedia of Genes and Genomes.

Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules. The major component of KEGG is the PATHWAY database that consists of graphical diagrams of biochemical pathways including most of the known metabolic pathways and some of the known regulatory pathways. The pathway information is also represented by the ortholog group tables summarizing orthologous and paralogous gene groups among different organisms. KEGG maintains the GENES database for the gene catalogs of all organisms with complete genomes and selected organisms with partial genomes, which are continuously re-annotated, as well as the LIGAND database for chemical compounds and enzymes. Each gene catalog is associated with the graphical genome map for chromosomal locations that is represented by Java applet. In addition to the data collection efforts, KEGG develops and provides various computational tools, such as for reconstructing biochemical pathways from the complete genome sequence and for predicting gene regulatory networks from the gene expression profiles. The KEGG databases are daily updated and made freely available (http://www.genome.ad.jp/kegg/).     

ATIDB: Arabidopsis thaliana insertion database

Insertional mutagenesis techniques, including transposon- and T-DNA-mediated mutagenesis, are key resources for systematic identification of gene function in the model plant species Arabidopsis thaliana. We have developed a database (http://atidb.cshl.org/) for archiving, searching and analyzing insertional mutagenesis lines. Flanking sequences from approximately 10 500 insertion lines (including transposon and T-DNA insertions) from several tagging programs in Arabidopsis were mapped to the genome sequence through our annotation system before being entered into the database. The database front end provides World Wide Web searching and analyzing interfaces for genome researchers and other biologists. Users can search the database to identify insertions in a particular gene or perform genome-wide analysis to study the distribution and preference of insertions. Tools integrated with the database include a graphical genome browser, a protein search function, a graphical representation of the insertion distribution and a Blast search function. The database is based on open source components and is available under an open source license.     

Comparing statistical methods for constructing large scale gene networks

The gene regulatory network (GRN) reveals the regulatory relationships among genes and can provide a systematic understanding of molecular mechanisms underlying biological processes. The importance of computer simulations in understanding cellular processes is now widely accepted; a variety of algorithms have been developed to study these biological networks. The goal of this study is to provide a comprehensive evaluation and a practical guide to aid in choosing statistical methods for constructing large scale GRNs. Using both simulation studies and a real application in E. coli data, we compare different methods in terms of sensitivity and specificity in identifying the true connections and the hub genes, the ease of use, and computational speed. Our results show that these algorithms performed reasonably well, and each method has its own advantages: (1) GeneNet, WGCNA (Weighted Correlation Network Analysis), and ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks) performed well in constructing the global network structure; (2) GeneNet and SPACE (Sparse PArtial Correlation Estimation) performed well in identifying a few connections with high specificity.     

A systems approach to morphogenesis in <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis>: I. AGNS database

In systems biology, study of a complex and multicomponent system, such as morphogenesis, comprises accumulation of data on morphogenetic processes in databases, classification and logical analysis of this information, and computer simulation of the processes in question using the data accumulated and the results of their analysis. This paper describes realization of the first steps in a systems study of morphogenesis (annotating research papers, compiling information in a database, data systematization, and their logical analysis) by the example of Arabidopsis thaliana, a model object in plant molecular biology. The database AGNS (Arabidopsis GeneNet Supplementary; http://wwwmgs.bionet.nsc.ru/agns) contains the experimentally confirmed information from published papers on specific features of gene expression and phenotypes of wild-type, mutant, and transgenic A. thaliana plants. AGNS queries and logical data analysis with the aid of specially developed software makes it possible to model various morphogenetic processes from gene expression to functioning of gene networks and their contribution to the development of certain traits.     

phiGENOME: an integrative navigation throughout bacteriophage genomes

phiGENOME is a web-based genome browser generating dynamic and interactive graphical representation of phage genomes stored in the phiSITE, database of gene regulation in bacteriophages. phiGENOME is an integral part of the phiSITE web portal (http://www.phisite.org/phigenome) and it was optimised for visualisation of phage genomes with the emphasis on the gene regulatory elements. phiGENOME consists of three components: (i) genome map viewer built using Adobe Flash technology, providing dynamic and interactive graphical display of phage genomes; (ii) sequence browser based on precisely formatted HTML tags, providing detailed exploration of genome features on the sequence level and (iii) regulation illustrator, based on Scalable Vector Graphics (SVG) and designed for graphical representation of gene regulations. Bringing 542 complete genome sequences accompanied with their rich annotations and references, makes phiGENOME a unique information resource in the field of phage genomics.     

Application of filter technology in photomorphogenesis gene network

Light regulates almost all physiological and biochemical processes in plants. Plants react to quantitative and qualitative light characteristics owing to the system of photoreceptors and a branched network for light signal transduction. Comprehensible visual representations of gene networks using of filter technology in the GeneNet system assist understanding the types of the relationships between the components inside the networks and to define their hierarchical structure.     

CADLIVE for constructing a large-scale biochemical network based on a simulation-directed notation and its application to yeast cell cycle

The further understanding of the mechanisms of gene regulatory networks requires comprehensive tools for both the representation of complicated signal transduction pathways and the in silico identification of genomic signals that govern the regulation of gene expression. Consequently, sophisticated notation must be developed to represent the signal transduction pathways in a form that can be readily processed by both computers and humans. We propose the regulator–reaction equations combined with detailed attributes including the associated cellular component, molecular function, and biological process and present the simulation-directed graphical notation that is derived from modification of Kohn’s method. We have developed the software suite, CADLIVE (Computer-Aided Design of LIVing systEms), which features a graphical user interface (GUI) to edit large-scale maps of complicated signal transduction pathways using a conventional XML-based representation. The regulator–reaction equations represent not only mechanistic reactions, but also semantic models containing ambiguous and incomplete processes. In order to demonstrate the feasibility of CADLIVE, we constructed a detailed map of the budding yeast cell cycle, which consists of 184 molecules and 152 reactions, in a really compact space. CADLIVE enables one to look at the whole view of a large-scale map, to integrate postgenomic data into the map, and to computationally simulate the signal transduction pathways, which greatly facilitates exploring novel or unexpected interactions.