VisANT: data-integrating visual framework for biological networks and modules

Abstract

VisANT is a web-based software framework for visualizing and analyzing many types of networks of biological interactions and associations. Networks are a useful computational tool for representing many types of biological data, such as biomolecular interactions, cellular pathways and functional modules. Given user-defined sets of interactions or groupings between genes or proteins, VisANT provides: (i) a visual interface for combining and annotating network data, (ii) supporting function and annotation data for different genomes from the Gene Ontology and KEGG databases and (iii) the statistical and analytical tools needed for extracting topological properties of the user-defined networks. Users can customize, modify, save and share network views with other users, and import basic network data representations from their own data sources, and from standard exchange formats such as PSI-MI and BioPAX. The software framework we employ also supports the development of more sophisticated visualization and analysis functions through its open API for Java-based plug-ins. VisANT is distributed freely via the web at http://visant.bu.edu and can also be downloaded for individual use.

Figure 1

Workflow of visualizing and analyzing networks with VisANT.

Figure 2

Gene Ontology function and protein–protein interaction mapping with VisANT. The colored regions contain genes and proteins annotated in the SGD yeast GO as belonging to molecular function categories of transcription activators (peach), transcription repressors (blue), DNA binding (magenta) and signal transduction (green). These functional groups can be expanded or collapsed by double-clicking with the mouse. Dark black connections between GO categories indicate shared gene or protein components of these functions, e.g. the protein alien appears both in signal transduction and in transcription activation. Gray connections are protein–protein interactions determined by high-throughput yeast two-hybrid assay by Giot et al. (18). Interactions of other types can be loaded by the user from their own sources, or from other methods in the database.

Figure 3

Dynamic linking for finding topological features. The network of synthetic lethal genetic interactions (28) in yeast contains 823 genes and 3952 interactions. A plot of the degree distribution of genes in this network allows users to quickly identify which genes have the highest (or lowest) connectivity. In this example, the gene shown is YDL029W, which has synthetic lethal interactions with 58 neighbors.