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DynOVis: a web tool to study dynamic perturbations for capturing dose-over-time effects in biological networks
T J M Kuijpers1, J E J Wolters2,3, J C S Kleinjans2
1Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, P.O. Box 616, Maastricht, 6200 MD, The Netherlands. tim.kuijpers@maastrichtuniversity.nl.
BMC Bioinformatics
|August 15, 2019
Summary
DynOVis is a new bioinformatics tool for visualizing dynamic biological networks. It helps researchers analyze complex cellular processes by showing dose-over-time effects and integrating gene and disease data.
Area of Science:
- Bioinformatics
- Systems Biology
- Computational Biology
Background:
- High-throughput sequencing generates large datasets of dynamic cellular processes.
- Analyzing dynamic biological data is challenging due to its complex nature.
- There is a need for specialized bioinformatics tools to analyze dynamic biological networks.
Purpose of the Study:
- To present DynOVis, a novel network visualization tool.
- To enable the analysis of dynamic dose-over-time effects in biological networks.
- To provide an accessible tool for visualizing dynamic biological perturbations.
Main Methods:
- DynOVis integrates R packages and JavaScript libraries.
- It employs a force-directed graph network style.
- Features include node expression animations and frame-by-frame dynamic exposure views.
Main Results:
- DynOVis visualizes dynamic perturbations in biological networks.
- It allows users to investigate temporal changes and dose-over-time effects.
- Integration with databases (ConsensusPathDB, CTD, NCBI) highlights biological relevance of network nodes.
Conclusions:
- DynOVis is a valuable tool for analyzing dynamic biological networks.
- It facilitates the visualization and investigation of temporal changes.
- Integrated data enhances the identification of biological significance, requiring no prior bioinformatics expertise.
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