TVNViewer: An interactive visualization tool for exploring networks that change over time or space

Curtis, Ross E.; Yuen, Amos; Song, Liang‐Nian; Goyal, Anuj; Xing, Eric P.

doi:10.1093/bioinformatics/btr273

Cited by 17 publications

(11 citation statements)

References 12 publications

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“…Statistical tests combining P value and z-score were used to detect overrepresentation of the annotations included in either GO, KEGG and CheA database. Transcription factor networks were created through the software TVNviewer 56 . Ingenuity Pathway Analysis was used to evaluate the enrichment of certain biological classes in protein with weak RNA to protein correlation.…”

Section: Methodsmentioning

confidence: 99%

Proteome adaptation in cell reprogramming proceeds via distinct transcriptional networks

et al. 2014

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The ectopic expression of Oct4, Klf4, c-Myc and Sox2 (OKMS) transcription factors allows reprogramming of somatic cells into induced pluripotent stem cells (iPSCs). The reprogramming process, which involves a complex network of molecular events, is not yet fully characterized. Here we perform a quantitative mass spectrometry-based analysis to probe in-depth dynamic proteome changes during somatic cell reprogramming. Our data reveal defined waves of proteome resetting, with the first wave occurring 48 h after the activation of the reprogramming transgenes and involving specific biological processes linked to the c-Myc transcriptional network. A second wave of proteome reorganization occurs in a later stage of reprogramming, where we characterize the proteome of two distinct pluripotent cellular populations. In addition, the overlay of our proteome resource with parallel generated -omics data is explored to identify post-transcriptionally regulated proteins involved in key steps during reprogramming.

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Section: Methodsmentioning

confidence: 99%

Proteome adaptation in cell reprogramming proceeds via distinct transcriptional networks

et al. 2014

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“…The 2D linear layout is adequate in looking at time traces of connections. The 2D circular layout, similar to Circos [18] or TVNViewer [12], serves well for individual time point analysis.…”

Section: Methodsmentioning

confidence: 99%

“…Time-focused visualization has been the object of different tools, like GATE [9], VistaClara [10], BioTapestry [11], TVNViewer [12], Arena3D [13,14], iPath [15] or iTOL [16]. These tools provide functionality for analyzing gene regulatory, metabolic, or protein–protein interaction networks that change with time.…”

Section: Introductionmentioning

confidence: 99%

PhenoTimer: Software for the Visual Mapping of Time-Resolved Phenotypic Landscapes

Secrier

Schneider

2013

PLoS ONE

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Timing common and specific modulators of disease progression is crucial for treatment, but the understanding of the underlying complex system of interactions is limited. While attempts at elucidating this experimentally have produced enormous amounts of phenotypic data, tools that are able to visualize and analyze them are scarce and the insight obtained from the data is often unsatisfactory. Linking and visualizing processes from genes to phenotypes and back, in a temporal context, remains a challenge in systems biology. We introduce PhenoTimer, a 2D/3D visualization tool for the mapping of time-resolved phenotypic links in a genetic context. It uses a novel visualization approach for relations between morphological defects, pathways or diseases, to enable fast pattern discovery and hypothesis generation. We illustrate its capabilities of tracing dynamic motifs on cell cycle datasets that explore the phenotypic order of events upon perturbations of the system, transcriptional activity programs and their connection to disease. By using this tool we are able to fine-grain regulatory programs for individual time points of the cell cycle and better understand which patterns arise when these programs fail. We also illustrate a way to identify common mechanisms of misregulation in diseases and drug abuse.

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“…A recently published tool on dynamic network visualization is the TVNViewer []. It does not offer any novel network layouts but its functionality allows the spatio‐temporal dynamics of a PPI network to be visualized as a multidimensional model.…”

Section: Dynamic Interactome Visualizationmentioning

confidence: 99%

“…the focus, selected by the investigator []. Figure provides an example generated from a synthetic cell cycle data set []. It shows the result of using the mouse pointer action to achieve details on demand by exposing protein members hidden within a GO node.…”

Section: Dynamic Interactome Visualizationmentioning

confidence: 99%

Visualization of the interactome: What are we looking at?

Fung

Goel

et al. 2012

Proteomics

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Network visualization of the interactome has been become routine in systems biology research. Not only does it serve as an illustration on the cellular organization of protein-protein interactions, it also serves as a biological context for gaining insights from high-throughput data. However, the challenges to produce an effective visualization have been great owing to the fact that the scale, biological context and dynamics of any given interactome are too large and complex to be captured by a single visualization. Visualization design therefore requires a pragmatic trade-off between capturing biological concept and being comprehensible. In this review, we focus on the biological interpretation of different network visualizations. We will draw on examples predominantly from our experiences but elaborate them in the context of the broader field. A rich variety of networks will be introduced including interactomes and the complexome in 2D, interactomes in 2.5D and 3D and dynamic networks.

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TVNViewer: An interactive visualization tool for exploring networks that change over time or space

Abstract: epxing@cs.cmu.edu.

Cited by 17 publications

References 12 publications

Proteome adaptation in cell reprogramming proceeds via distinct transcriptional networks

Proteome adaptation in cell reprogramming proceeds via distinct transcriptional networks

PhenoTimer: Software for the Visual Mapping of Time-Resolved Phenotypic Landscapes

Visualization of the interactome: What are we looking at?

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