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linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser
In biology, we are often confronted with information-rich, large-scale trajectory data, but exploring and communicating patterns in such data can be a cumbersome task. Ideally, the data should be wrapped with an interactive visualisation in one concise packet that makes it straightforward to create...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8584757/ https://www.ncbi.nlm.nih.gov/pubmed/34723958 http://dx.doi.org/10.1371/journal.pcbi.1009503 |
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author | Waschke, Johannes Hlawitschka, Mario Anlas, Kerim Trivedi, Vikas Roeder, Ingo Huisken, Jan Scherf, Nico |
author_facet | Waschke, Johannes Hlawitschka, Mario Anlas, Kerim Trivedi, Vikas Roeder, Ingo Huisken, Jan Scherf, Nico |
author_sort | Waschke, Johannes |
collection | PubMed |
description | In biology, we are often confronted with information-rich, large-scale trajectory data, but exploring and communicating patterns in such data can be a cumbersome task. Ideally, the data should be wrapped with an interactive visualisation in one concise packet that makes it straightforward to create and test hypotheses collaboratively. To address these challenges, we have developed a tool, linus, which makes the process of exploring and sharing 3D trajectories as easy as browsing a website. We provide a python script that reads trajectory data, enriches them with additional features such as edge bundling or custom axes, and generates an interactive web-based visualisation that can be shared online. linus facilitates the collaborative discovery of patterns in complex trajectory data. |
format | Online Article Text |
id | pubmed-8584757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-85847572021-11-12 linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser Waschke, Johannes Hlawitschka, Mario Anlas, Kerim Trivedi, Vikas Roeder, Ingo Huisken, Jan Scherf, Nico PLoS Comput Biol Research Article In biology, we are often confronted with information-rich, large-scale trajectory data, but exploring and communicating patterns in such data can be a cumbersome task. Ideally, the data should be wrapped with an interactive visualisation in one concise packet that makes it straightforward to create and test hypotheses collaboratively. To address these challenges, we have developed a tool, linus, which makes the process of exploring and sharing 3D trajectories as easy as browsing a website. We provide a python script that reads trajectory data, enriches them with additional features such as edge bundling or custom axes, and generates an interactive web-based visualisation that can be shared online. linus facilitates the collaborative discovery of patterns in complex trajectory data. Public Library of Science 2021-11-01 /pmc/articles/PMC8584757/ /pubmed/34723958 http://dx.doi.org/10.1371/journal.pcbi.1009503 Text en © 2021 Waschke et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Waschke, Johannes Hlawitschka, Mario Anlas, Kerim Trivedi, Vikas Roeder, Ingo Huisken, Jan Scherf, Nico linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser |
title | linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser |
title_full | linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser |
title_fullStr | linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser |
title_full_unstemmed | linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser |
title_short | linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser |
title_sort | linus: conveniently explore, share, and present large-scale biological trajectory data in a web browser |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8584757/ https://www.ncbi.nlm.nih.gov/pubmed/34723958 http://dx.doi.org/10.1371/journal.pcbi.1009503 |
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