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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,\n                    <jats:italic>linus<\/jats:italic>\n                    , 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.\n                    <jats:italic>linus<\/jats:italic>\n                    facilitates the collaborative discovery of patterns in complex trajectory data.\n                  <\/jats:p>","DOI":"10.1371\/journal.pcbi.1009503","type":"journal-article","created":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T13:32:57Z","timestamp":1635773577000},"page":"e1009503","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["linus: Conveniently explore, share, and present large-scale biological trajectory data in a web 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