13 research outputs found

    IntegromeDB: an integrated system and biological search engine

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    Abstract Background With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Description Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. Conclusions The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback

    BiologicalNetworks 2.0 - an integrative view of genome biology data

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    Abstract Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org

    BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies

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    <p>Abstract</p> <p>Background</p> <p>Understanding of immune response mechanisms of pathogen-infected host requires multi-scale analysis of genome-wide data. Data integration methods have proved useful to the study of biological processes in model organisms, but their systematic application to the study of host immune system response to a pathogen and human disease is still in the initial stage.</p> <p>Results</p> <p>To study host-pathogen interaction on the systems biology level, an extension to the previously described BiologicalNetworks system is proposed. The developed methods and data integration and querying tools allow simplifying and streamlining the process of integration of diverse experimental data types, including molecular interactions and phylogenetic classifications, genomic sequences and protein structure information, gene expression and virulence data for pathogen-related studies. The data can be integrated from the databases and user's files for both public and private use.</p> <p>Conclusions</p> <p>The developed system can be used for the systems-level analysis of host-pathogen interactions, including host molecular pathways that are induced/repressed during the infections, co-expressed genes, and conserved transcription factor binding sites. Previously unknown to be associated with the influenza infection genes were identified and suggested for further investigation as potential drug targets. Developed methods and data are available through the Java application (from BiologicalNetworks program at <url>http://www.biologicalnetworks.org</url>) and web interface (at <url>http://flu.sdsc.edu</url>).</p

    The effect of soil on spatial variation of the herbaceous layer modulated by overstorey in an Eastern European poplar-willow forest

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    The tree species composition can influence the dynamics of herbaceous species and enhance the spatial heterogeneity of the soil. But there is very little evidence on how both overstorey structure and soil properties affect the spatial variation of the herb layer. The aim of this study is to evaluate the factors of the soil and overstorey structure by which it is possible to explain the fine-scale variation of herbaceous layer communities in an Eastern European poplar-willow forest. The research was conducted in the “Dnipro-Orils’kiy” Nature Reserve (Ukraine). The research polygon (48°30′51″N, 34°49″02″E) was laid in an Eastern European poplar-willow forest in the floodplain of the River Protich, which is a left inflow of the River Dnipro. The site consists of 7 transects. Each transect was made up of 15 test points. The distance between rows in the site was 3 m. At the site, we established a plot of 45×21 m, with 105 subplots of 3×3 m organized in a regular grid. The adjacent subplots were in close proximity. Vascular plant species lists were recorded at each 3×3 m subplot along with visual estimates of species cover using the nine-degree Braun-Blanquet scale. Within the plot, all woody stems ≥ 1 cm in diameter at breast height were measured and mapped. Dixon’s segregation index was calculated for tree species to quantify their relative spatial mixing. Based on geobotanical descriptions, a phytoindicative assessment of environmental factors according to the Didukh scale was made. The redundancy analysis was used for the analysis of variance in the herbaceous layer species composition. The geographic coordinates of sampling locations were used to generate a set of orthogonal eigenvector-based spatial variables. Two measurements of the overstorey spatial structure were applied: the distances from the nearest tree of each species and the distance based on the evaluation of spatial density of point objects, which are separate trees. In both cases, the distance matrix of sampling locations was calculated, which provided the opportunity to generate eigenvector-based spatial variables. A kernel smoothed intensity function was used to compute the density of the trees’ spatial distribution from the point patterns’ data. Gaussian kernel functions with various bandwidths were used. The coordinates of sampling locations in the space obtained after the conversion of the trees’ spatial distribution densities were used to generate a set of orthogonal eigenvector-based spatial variables, each of them representing a pattern of particular scale within the extent of the bandwidth area structured according to distance and reciprocal placement of the trees. An overall test of random labelling reveals the total nonrandom distribution of the tree stems within the site. The unexplained variation consists of 43.8%. The variation explained solely by soil variables is equal to 15.5%, while the variation explained both by spatial and soil variables is 18.0%. The measure of the overstorey spatial structure, which is based on the evaluation of its density enables us to obtain different estimations depending on the bandwidth. The bandwidth affects the explanatory capacity of the tree stand. A considerable part of the plant community variation explained by soil factors was spatially structured. The orthogonal eigenvector-based spatial variables (dbMEMs) approach can be extended to quantifying the effect of forest structures on the herbaceous layer community. The measure of the overstorey spatial structure, which is based on the evaluation of its density, was very useful in explaining herbaceous layer community variation

    IntegromeDB: an integrated system and biological search engine

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    Abstract Background With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Description Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. Conclusions The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback.</p

    Phylogenetic Diversity of Plant Metacommunity of the Dnieper River Arena Terrace Within the ‘Dnieper-Orilskiy ’ Nature Reserve

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    This article presents the features of the phylogenetic organization of the plant communities of the Dnieper River terrace within the ‘Dnieper-Orilskiy’ Nature Reserve and the patterns of its spatial variation involving remote sensing data of the Earth’s surface. The research materials were collected in the period 2012−2016 from within the nature reserve. The research polygon is within the first terrace (arena) of the Dnieper valley. Sandy steppe, meadow, forest and marsh communities within the Protoch river floodplain and the Orlova ravine, as well as artificial pine plantations were the habitats present within the research polygon. The vegetation description was carried out on 10×10 m (100 m2) plots. A total of 94 geobotanical descriptions were made. Data on plant phylogeny was obtained by the Phylomatic service. Phylogenetic diversity of the communities was assessed by the Faith, Simpson and Shannon indices. Phylogenetic analysis was performed by means of a double principal coordinate analysis (DPCoA). The vegetation cover within the investigated polygon was represented by 189 species. Abundance Phylogenetic Deviation (APD) for the investigated metacommunity was evaluated to −0.53, which is statistically significantly different from random alternatives (p = 0.001). The APD negative value indicates that phylogenetic organization of the investigated metacommunity is overdispersed. The permutation procedure allowed us to establish that the eigenvalues of the DPCoA-axes obtained as a result of the real phylogenetic tree were significantly higher than their own number for the random phylogenetic trees for the first seven axes. This indicates that the first seven axes are useful for additional information on the ordination structure of the metacommunity

    BiologicalNetworks 2.0 - an integrative view of genome biology data

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    Abstract Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org.</p
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