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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
Published on: December 7, 2021
Dynamic visualization of expressed gene networks
Ingrid Remy1, Stephen W Michnick
1Département de Biochimie, Université de Montréal, succursale centre-ville, Montréal, Québec, Canada.
Abstract:
Cellular biochemical machineries, what we call pathways, consist of dynamically assembling and disassembling macromolecular complexes. While our models for the organization of biochemical machines are derived largely from in vitro experiments, do they reflect their organization in living cells? We have developed a general experimental strategy that addresses this question by allowing the quantitative probing of molecular interactions in intact living cells. The experimental strategy is based on protein fragment complementation assays (PCA), a method whereby protein interactions are coupled to refolding of enzymes from cognate fragments where reconstitution of enzyme activity acts as the detector of a protein interaction. A biochemical machine or pathway is defined by grouping interacting proteins into those that are perturbed in the same way by common factors (hormones, metabolites, enzyme inhibitors, etc). In this review, we describe how we go from descriptive to quantitative representations of biochemical networks at an individual to whole genome level and how our approach will lead ultimately to better descriptions of the biochemical machineries that underlie living processes.
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