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...

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Autores principales:	Johannes Waschke, Mario Hlawitschka, Kerim Anlas, Vikas Trivedi, Ingo Roeder, Jan Huisken, Nico Scherf
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/b5a0ed5bb1d9464189b5206b3878d55f
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id	oai:doaj.org-article:b5a0ed5bb1d9464189b5206b3878d55f
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spelling	oai:doaj.org-article:b5a0ed5bb1d9464189b5206b3878d55f2021-12-02T19:57:40Zlinus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser.1553-734X1553-735810.1371/journal.pcbi.1009503https://doaj.org/article/b5a0ed5bb1d9464189b5206b3878d55f2021-11-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009503https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358In 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.Johannes WaschkeMario HlawitschkaKerim AnlasVikas TrivediIngo RoederJan HuiskenNico ScherfPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 11, p e1009503 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Johannes Waschke Mario Hlawitschka Kerim Anlas Vikas Trivedi Ingo Roeder Jan Huisken Nico Scherf linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser.
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	article
author	Johannes Waschke Mario Hlawitschka Kerim Anlas Vikas Trivedi Ingo Roeder Jan Huisken Nico Scherf
author_facet	Johannes Waschke Mario Hlawitschka Kerim Anlas Vikas Trivedi Ingo Roeder Jan Huisken Nico Scherf
author_sort	Johannes Waschke
title	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_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_sort	linus: conveniently explore, share, and present large-scale biological trajectory data in a web browser.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/b5a0ed5bb1d9464189b5206b3878d55f
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linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser.

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