Zhenjun Hu

The BioPAX community standard for pathway data sharing

Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.

VisANT: an online visualization and analysis tool for biological interaction data

BackgroundNew techniques for determining relationships between biomolecules of all types – genes, proteins, noncoding DNA, metabolites and small molecules – are now making a substantial contribution to the widely discussed explosion of facts about the cell. The data generated by these techniques promote a picture of the cell as an interconnected information network, with molecular components linked with one another in topologies that can encode and represent many features of cellular function. This networked view of biology brings the potential for systematic understanding of living molecular systems.ResultsWe present VisANT, an application for integrating biomolecular interaction data into a cohesive, graphical interface. This software features a multi-tiered architecture for data flexibility, separating back-end modules for data retrieval from a front-end visualization and analysis package. VisANT is a freely available, open-source tool for researchers, and offers an online interface for a large range of published data sets on biomolecular interactions, including those entered by users. This system is integrated with standard databases for organized annotation, including GenBank, KEGG and SwissProt. VisANT is a Java-based, platform-independent tool suitable for a wide range of biological applications, including studies of pathways, gene regulation and systems biology.ConclusionVisANT has been developed to provide interactive visual mining of biological interaction data sets. The new software provides a general tool for mining and visualizing such data in the context of sequence, pathway, structure, and associated annotations. Interaction and predicted association data can be combined, overlaid, manipulated and analyzed using a variety of built-in functions. VisANT is available at http://visant.bu.edu.

Genome-wide prioritization of disease genes and identification of disease-disease associations from an integrated human functional linkage network

We integrate 16 genomic features to construct an evidence-weighted functional-linkage network comprising 21,657 human genes. The functional-linkage network is used to prioritize candidate genes for 110 diseases, and to reliably disclose hidden associations between disease pairs having dissimilar phenotypes, such as hypercholesterolemia and Alzheimers disease. Many of these disease-disease associations are supported by epidemiology, but with no previous genetic basis. Such associations can drive novel hypotheses on molecular mechanisms of diseases and therapies.

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

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 and can also be downloaded for individual use.

VisANT 3.5: multi-scale network visualization, analysis and inference based on the gene ontology

Despite its wide usage in biological databases and applications, the role of the gene ontology (GO) in network analysis is usually limited to functional annotation of genes or gene sets with auxiliary information on correlations ignored. Here, we report on new capabilities of VisANT--an integrative software platform for the visualization, mining, analysis and modeling of the biological networks--which extend the application of GO in network visualization, analysis and inference. The new VisANT functions can be classified into three categories. (i) Visualization: a new tree-based browser allows visualization of GO hierarchies. GO terms can be easily dropped into the network to group genes annotated under the term, thereby integrating the hierarchical ontology with the network. This facilitates multi-scale visualization and analysis. (ii) Flexible annotation schema: in addition to conventional methods for annotating network nodes with the most specific functional descriptions available, VisANT also provides functions to annotate genes at any customized level of abstraction. (iii) Finding over-represented GO terms and expression-enriched GO modules: two new algorithms have been implemented as VisANT plugins. One detects over-represented GO annotations in any given sub-network and the other finds the GO categories that are enriched in a specified phenotype or perturbed dataset. Both algorithms take account of network topology (i.e. correlations between genes based on various sources of evidence). VisANT is freely available at http://visant.bu.edu.

The COMBREX Project: Design, Methodology, and Initial Results

Experimental data exists for only a vanishingly small fraction of sequenced microbial genes. This community page discusses the progress made by the COMBREX project to address this important issue using both computational and experimental resources.

Gene set enrichment analysis: performance evaluation and usage guidelines

A central goal of biology is understanding and describing the molecular basis of plasticity: the sets of genes that are combinatorially selected by exogenous and endogenous environmental changes, and the relations among the genes. The most viable current approach to this problem consists of determining whether sets of genes are connected by some common theme, e.g. genes from the same pathway are overrepresented among those whose differential expression in response to a perturbation is most pronounced. There are many approaches to this problem, and the results they produce show a fair amount of dispersion, but they all fall within a common framework consisting of a few basic components. We critically review these components, suggest best practices for carrying out each step, and propose a voting method for meeting the challenge of assessing different methods on a large number of experimental data sets in the absence of a gold standard.

VisANT: an integrative framework for networks in systems biology

The essence of a living cell is adaptation to a changing environment, and a central goal of modern cell biology is to understand adaptive change under normal and pathological conditions. Because the number of components is large, and processes and conditions are many, visual tools are useful in providing an overview of relations that would otherwise be far more difficult to assimilate. Historically, representations were static pictures, with genes and proteins represented as nodes, and known or inferred correlations between them (links) represented by various kinds of lines. The modern challenge is to capture functional hierarchies and adaptation to environmental change, and to discover pathways and processes embedded in known data, but not currently recognizable. Among the tools being developed to meet this challenge is VisANT (freely available at http://visant.bu.edu) which integrates, mines and displays hierarchical information. Challenges to integrating modeling (discrete or continuous) and simulation capabilities into such visual mining software are briefly discussed.

VisANT 4.0: Integrative network platform to connect genes, drugs, diseases and therapies

With the rapid accumulation of our knowledge on diseases, disease-related genes and drug targets, network-based analysis plays an increasingly important role in systems biology, systems pharmacology and translational science. The new release of VisANT aims to provide new functions to facilitate the convenient network analysis of diseases, therapies, genes and drugs. With improved understanding of the mechanisms of complex diseases and drug actions through network analysis, novel drug methods (e.g., drug repositioning, multi-target drug and combination therapy) can be designed. More specifically, the new update includes (i) integrated search and navigation of disease and drug hierarchies; (ii) integrated disease–gene, therapy–drug and drug–target association to aid the network construction and filtering; (iii) annotation of genes/drugs using disease/therapy information; (iv) prediction of associated diseases/therapies for a given set of genes/drugs using enrichment analysis; (v) network transformation to support construction of versatile network of drugs, genes, diseases and therapies; (vi) enhanced user interface using docking windows to allow easy customization of node and edge properties with build-in legend node to distinguish different node type. VisANT is freely available at: http://visant.bu.edu.

VisANT 3.0: new modules for pathway visualization, editing, prediction and construction

With the integration of the KEGG and Predictome databases as well as two search engines for coexpressed genes/proteins using data sets obtained from the Stanford Microarray Database (SMD) and Gene Expression Omnibus (GEO) database, VisANT 3.0 supports exploratory pathway analysis, which includes multi-scale visualization of multiple pathways, editing and annotating pathways using a KEGG compatible visual notation and visualization of expression data in the context of pathways. Expression levels are represented either by color intensity or by nodes with an embedded expression profile. Multiple experiments can be navigated or animated. Known KEGG pathways can be enriched by querying either coexpressed components of known pathway members or proteins with known physical interactions. Predicted pathways for genes/proteins with unknown functions can be inferred from coexpression or physical interaction data. Pathways produced in VisANT can be saved as computer-readable XML format (VisML), graphic images or high-resolution Scalable Vector Graphics (SVG). Pathways in the format of VisML can be securely shared within an interested group or published online using a simple Web link. VisANT is freely available at http://visant.bu.edu.