Interactive visualization of gene regulatory networks with associated gene expression time series data We present GENeVis, an application to visualize gene expression time series data in a gene regulatory network context. This is a network of regulator proteins that regulate the expression of their respective target genes. The networks are represented as graphs, in which the nodes represent genes, and the edges represent interactions between a gene and its targets. GENeVis adds features that are currently lacking in existing tools, such as mapping of expression value and corresponding p-value (or other statistic) to a single visual attribute, multiple time point visualization, and visual comparison of multiple time series in one view. Various interaction mechanisms, such as panning, zooming, regulator and target highlighting, data selection, and tooltips support data analysis and exploration. Subnetworks can be studied in detail in a separate view that shows the network context, expression data plots, and tables containing the raw expression data. We present a case study, in which gene expression time series data acquired in-house are analyzed by a biological expert using GENeVis. The case study shows that the application fills the gap between present biological interpretation of time series experiments, performed on a gene-by-gene basis, and analysis of global classes of genes whose expression is regulated by regulator proteins.
References in zbMATH (referenced in 2 articles , 1 standard article )
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- Guo, Xiaoyang; Srivastava, Anuj; Sarkar, Sudeep: A quotient space formulation for generative statistical analysis of graphical data (2021)
- Westenberg, Michel A.; van Hijum, Sacha A. F. T.; Lulko, Andrzej T.; Kuipers, Oscar P.; Roerdink, Jos B. T. M.: Interactive visualization of gene regulatory networks with associated gene expression time series data (2008)