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Updated: Jul 13, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
Published on: December 7, 2021
MOVE: a multi-level ontology-based visualization and exploration framework for genomic networks
Diederik W J Bosman1, Evert-Jan Blom, Patrick J Ogao
1Institute for Mathematics and Computing Science, University of Groningen, Netherlands.
Abstract:
Among the various research areas that comprise bioinformatics, systems biology is gaining increasing attention. An important goal of systems biology is the unraveling of dynamic interactions between components of living cells (e. g., proteins, genes). These interactions exist among others on genomic, transcriptomic, proteomic and metabolomic levels. The levels themselves are heavily interconnected, resulting in complex networks of different interacting biological entities. Currently, various bioinformatics tools exist which are able to perform a particular analysis on a particular type of network. Unfortunately, each tool has its own disadvantages hampering it to be used consistently for different types of networks or analytical methods. This paper describes the conceptual development of an open source extensible software framework that supports visualization and exploration of highly complex genomic networks, like metabolic or gene regulatory networks. The focus is on the conceptual foundations, starting from requirements, a description of the state of the art of network visualization systems, and an analysis of their shortcomings. We describe the implementation of some initial modules of the framework and apply them to a biological test case in bacterial regulation, which shows the relevance and feasibility of the proposed approach.
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