Recent advances with high-throughput methods in life-science research have increased
the need for automatized data analysis and visual exploration techniques. Sophisticated
bioinformatics tools are essential to deduct biologically meaningful interpretations
from the large amount of experimental data, and help to understand biological processes.
We present VANTED, a tool for the
etworks with related
ata. Data from large-scale biochemical experiments is uploaded into the software via
a Microsoft Excel-based form. Then it can be mapped on a network that is either drawn
with the tool itself, downloaded from the KEGG Pathway database, or imported using
standard network exchange formats. Transcript, enzyme, and metabolite data can be
presented in the context of their underlying networks, e. g. metabolic pathways or
classification hierarchies. Visualization and navigation methods support the visual
exploration of the data-enriched networks. Statistical methods allow analysis and
comparison of multiple data sets such as different developmental stages or genetically
different lines. Correlation networks can be automatically generated from the data
and substances can be clustered according to similar behavior over time. As examples,
metabolite profiling and enzyme activity data sets have been visualized in different
metabolic maps, correlation networks have been generated and similar time patterns
detected. Some relationships between different metabolites were discovered which are
in close accordance with the literature.
VANTED greatly helps researchers in the analysis and interpretation of biochemical
data, and thus is a useful tool for modern biological research. VANTED as a Java Web
Start Application including a user guide and example data sets is available free of
charge at http://vanted.ipk-gatersleben.dewebcite.