PLoS Computational BiologyBioinformaticsPeer-reviewed journal article
linus: Conveniently explore, share and present large-scale biological trajectory data from a web browser.
Johannes WaschkeiD, Mario HlawitschkaiD, Kerim AnlaşiD, Vikas TrivediiD, Ingo RoederiD, Jan HuiskeniD, Nico ScherfiD
Abstract
In biology, we are often confronted with information-rich, large-scale trajectory data, but exploring and communicating patterns in such data is often a cumbersome task. Ideally, the data should be wrapped with an interactive visualisation in one concise package 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 and enriches them with additional features, such as edge bundling or custom axes and generates an interactive web-based visualisation that can be shared offline and online. The goal of linus is to facilitate the collaborative discovery of patterns in complex trajectory data.
- Citations
- 3
- FWCI
- 0.27
- Field percentile
- top 49%
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