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


Journal

Journal of visualized experiments : JoVE
ISSN: 1940-087X
Titre abrégé: J Vis Exp
Pays: United States
ID NLM: 101313252

Informations de publication

Date de publication:
07 12 2021
Historique:
entrez: 27 12 2021
pubmed: 28 12 2021
medline: 6 4 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 34958073
doi: 10.3791/63084
pmc: PMC8991438
mid: NIHMS1785926
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S. Video-Audio Media

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NIGMS NIH HHS
ID : R01 GM126555
Pays : United States
Organisme : NICHD NIH HHS
ID : T32 HD040372
Pays : United States

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Auteurs

Robert C Moseley (RC)

Department of Biology, Duke University; robert.moseley@duke.edu.

Sophia Campione (S)

Department of Biology, Duke University.

Bree Cummins (B)

Department of Mathematical Sciences, Montana State University.

Francis Motta (F)

Department of Mathematical Sciences, Florida Atlantic University.

Steven B Haase (SB)

Department of Biology, Duke University.

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Classifications MeSH