Skip to main content

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline.

Publication ,  Journal Article
Moseley, RC; Campione, S; Cummins, B; Motta, F; Haase, SB
Published in: Journal of visualized experiments : JoVE
December 2021

Developing gene regulatory network models is a major challenge in systems biology. Several computational tools and pipelines have been developed to tackle this challenge, including the newly developed Inherent Dynamics Pipeline. The Inherent Dynamics Pipeline consists of several previously published tools that work synergistically and are connected in a linear fashion, where the output of one tool is then used as input for the following tool. As with most computational techniques, each step of the Inherent Dynamics Pipeline requires the user to make choices about parameters that don't have a precise biological definition. These choices can substantially impact gene regulatory network models produced by the analysis. For this reason, the ability to visualize and explore the consequences of various parameter choices at each step can help increase confidence in the choices and the results.The Inherent Dynamics Visualizer is a comprehensive visualization package that streamlines the process of evaluating parameter choices through an interactive interface within a web browser. The user can separately examine the output of each step of the pipeline, make intuitive changes based on visual information, and benefit from the automatic production of necessary input files for the Inherent Dynamics Pipeline. The Inherent Dynamics Visualizer provides an unparalleled level of access to a highly intricate tool for the discovery of gene regulatory networks from time series transcriptomic data.

Duke Scholars

Published In

Journal of visualized experiments : JoVE

DOI

EISSN

1940-087X

ISSN

1940-087X

Publication Date

December 2021

Issue

178

Related Subject Headings

  • Transcriptome
  • Software
  • Gene Regulatory Networks
  • Computational Biology
  • 3101 Biochemistry and cell biology
  • 1702 Cognitive Sciences
  • 1701 Psychology
  • 0601 Biochemistry and Cell Biology
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Moseley, R. C., Campione, S., Cummins, B., Motta, F., & Haase, S. B. (2021). Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline. Journal of Visualized Experiments : JoVE, (178). https://doi.org/10.3791/63084
Moseley, Robert C., Sophia Campione, Bree Cummins, Francis Motta, and Steven B. Haase. “Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline.Journal of Visualized Experiments : JoVE, no. 178 (December 2021). https://doi.org/10.3791/63084.
Moseley RC, Campione S, Cummins B, Motta F, Haase SB. Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline. Journal of visualized experiments : JoVE. 2021 Dec;(178).
Moseley, Robert C., et al. “Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline.Journal of Visualized Experiments : JoVE, no. 178, Dec. 2021. Epmc, doi:10.3791/63084.
Moseley RC, Campione S, Cummins B, Motta F, Haase SB. Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline. Journal of visualized experiments : JoVE. 2021 Dec;(178).

Published In

Journal of visualized experiments : JoVE

DOI

EISSN

1940-087X

ISSN

1940-087X

Publication Date

December 2021

Issue

178

Related Subject Headings

  • Transcriptome
  • Software
  • Gene Regulatory Networks
  • Computational Biology
  • 3101 Biochemistry and cell biology
  • 1702 Cognitive Sciences
  • 1701 Psychology
  • 0601 Biochemistry and Cell Biology