Cargando…

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

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 visual...

Descripción completa

Detalles Bibliográficos
Autores principales: Secrier, Maria, Schneider, Reinhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3741141/
https://www.ncbi.nlm.nih.gov/pubmed/23951317
http://dx.doi.org/10.1371/journal.pone.0072361
_version_ 1782280203743002624
author Secrier, Maria
Schneider, Reinhard
author_facet Secrier, Maria
Schneider, Reinhard
author_sort Secrier, Maria
collection PubMed
description 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.
format Online
Article
Text
id pubmed-3741141
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-37411412013-08-15 PhenoTimer: Software for the Visual Mapping of Time-Resolved Phenotypic Landscapes Secrier, Maria Schneider, Reinhard PLoS One Research Article 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. Public Library of Science 2013-08-12 /pmc/articles/PMC3741141/ /pubmed/23951317 http://dx.doi.org/10.1371/journal.pone.0072361 Text en © 2013 Secrier et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Secrier, Maria
Schneider, Reinhard
PhenoTimer: Software for the Visual Mapping of Time-Resolved Phenotypic Landscapes
title PhenoTimer: Software for the Visual Mapping of Time-Resolved Phenotypic Landscapes
title_full PhenoTimer: Software for the Visual Mapping of Time-Resolved Phenotypic Landscapes
title_fullStr PhenoTimer: Software for the Visual Mapping of Time-Resolved Phenotypic Landscapes
title_full_unstemmed PhenoTimer: Software for the Visual Mapping of Time-Resolved Phenotypic Landscapes
title_short PhenoTimer: Software for the Visual Mapping of Time-Resolved Phenotypic Landscapes
title_sort phenotimer: software for the visual mapping of time-resolved phenotypic landscapes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3741141/
https://www.ncbi.nlm.nih.gov/pubmed/23951317
http://dx.doi.org/10.1371/journal.pone.0072361
work_keys_str_mv AT secriermaria phenotimersoftwareforthevisualmappingoftimeresolvedphenotypiclandscapes
AT schneiderreinhard phenotimersoftwareforthevisualmappingoftimeresolvedphenotypiclandscapes