BiologicalNetworks 2.0--an integrative view of genome biology data

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.

Figure 1

Integrative view of data in BiologicalNetworks.

Figure 2

Biological Themes. Biological Themes (GO terms, diseases, cell types, tissues, curated pathways, phenotypes and human anatomy) representation in BiologicalNetworks.

Figure 3

Genomic Sequence Analysis Browser and Annotations. (A) Using the Sequence Search (at the left) box, the user finds genes in Sequence Browser. In addition to gene related information, all regulatory regions integrated in the database are represented in Sequence Analysis Browser. (B) In addition to annotations integrated from public databases, BiologicalNetworks allows users to annotate genomic sequences. Annotation Tab and two ontologies used for annotation are represented. (C) Sequence intervals are connected to BioNets Ontology (in this case to Sequence Ontology) nodes through the internal Objects and Attribute values tables that list objects and attributes of different types integrated in the BiologicalNetworks database.

Figure 4

Screen-shot of Comparative Genomix Browser. Comparative Genomix Browser shown together with the pathway window that depicts transcription factor-DNA binding network for CREB, NRSF, GATA-1, ATF-1 (green squares) and their targets (red circles). In Comparative Genomix Browser (right window), for selected species, TFBSs collected from public data and predicted using phylogenetic footprinting are shown aligned as provided by phylogenetic footprinting. The user can zoom in/out, scroll the sequences and network regions for respective TFs and genes to see the binding sites, relative chromosomal positions of target genes and respective sequence events.

Figure 5

BiologicalNetworks data querying environment. (A) BuildPathwayWizard (BPW) assists the user in finding regulatory paths and functional links, between selected objects, searches for common targets or regulators for the group of molecules, finds connection to curated pathways (e.g. KEGG). BPW can find functional links between proteins in the lists imported from other programs (e.g. gene expression clusters). (B) Specialized Search Boxes are available on the Microarrays, Curated Pathways and Networks panels. (C) Search by attributes provides an advanced querying facility for retrieving the data of user's interest by querying Objects and Properties types. User friendly querying interface allows user to make query with any logical combination of conditions both on Node and Property types. (D) Organism Filter on 21 mostly used organisms and organism groups.

Figure 6

Systems analysis in BiologicalNetworks.The figure details the strategy that was used to systematically search for co-expressed (co-regulated) genes and promoter frameworks linked to the co-regulation of genes significant in hypertension in human, mouse and rat.

Figure 7

Integrated molecular interaction network of human/mouse/rat hypertension. Red rectangles - highly co-expressed (red lines) and over-expressed genes in hypertension. Yellow triangles - TFs potentially regulating hypertension-specific genes, which TF binding sites are conserved in human, mouse and rat. Black lines - physical protein/TF/kinase - protein/TF/kinase interactions. Green and Blue squares - genes/proteins/TFs that are well known from literature to be essential in hypertension. Red lines - co-expressed genes/proteins. Dashed lines - predicted TFs and their target genes. Numbers (1-4) correspond to gene/protein groups functionally enriched by particular GO terms, shown in the upper left corner.