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Preprint . 2020
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Preprint . 2020
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FAIR sharing of molecular visualization experiences: from pictures in the cloud to collaborative virtual reality exploration in immersive 3D environments

Authors: Baaden, Marc; Martinez, Xavier;

FAIR sharing of molecular visualization experiences: from pictures in the cloud to collaborative virtual reality exploration in immersive 3D environments

Abstract

Abstract Motivated by the current Covid-19 pandemic that has spurred a substantial flow of structural data we describe how molecular visualization experiences can be used to make these datasets accessible to a broad audience. Using a variety of technology vectors related to the cloud, 3D- and virtual reality gear, we examine how to share curated visualizations of structural biology, modeling and/or bioinformatics datasets for interactive and collaborative exploration. We discuss F.A.I.R. as overarching principle for sharing such visualizations. We provide four initial example scenes related to recent Covid-19 structural data together with a ready-to-use (and share) implementation in the UnityMol software. Synopsis Visualization renders structural molecular data accessible to a broad audience. We describe an approach to share molecular visualization experiences based on FAIR principles. Our workflow is exemplified with recent Covid-19 related data.

Keywords

COVID_19, unitymol, FAIR

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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