scholarly journals UnityMol prototype for FAIR sharing of molecular-visualization experiences: from pictures in the cloud to collaborative virtual reality exploration in immersive 3D environments

2021 ◽  
Vol 77 (6) ◽  
Author(s):  
Xavier Martinez ◽  
Marc Baaden
Keyword(s):  
Virtual Reality ◽  
Structural Biology ◽  
Structural Data ◽  
Data Sets ◽  
Molecular Visualization ◽  
Broad Audience ◽  
Collaborative Virtual Reality ◽  
3D Environments ◽  
Collaborative Exploration ◽  
Fair Sharing

Motivated by the current COVID-19 pandemic, which has spurred a substantial flow of structural data, the use of molecular-visualization experiences to make these data sets accessible to a broad audience is described. Using a variety of technology vectors related to the cloud, 3D and virtual reality gear, how to share curated visualizations of structural biology, modeling and/or bioinformatics data sets for interactive and collaborative exploration is examined. FAIR is discussed as an overarching principle for sharing such visualizations. Four initial example scenes related to recent COVID-19 structural data are provided, together with a ready-to-use (and share) implementation in the UnityMol software.

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

2020 ◽  
Author(s):  
Xavier Martinez ◽  
Marc Baaden
Keyword(s):  
Virtual Reality ◽  
Structural Data ◽  
Molecular Data ◽  
Molecular Visualization ◽  
Related Data ◽  
Broad Audience ◽  
Collaborative Virtual Reality ◽  
3D Environments ◽  
Fair Principles ◽  
Collaborative Exploration

AbstractMotivated 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.SynopsisVisualization 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.

A COLLABORATIVE VIRTUAL REALITY ENVIRONMENT FOR NEUROSURGICAL PLANNING AND TRAINING

2007 ◽  
Vol 61 ◽  
pp. 379-391 ◽  
Author(s):  
Ralf A. Kockro ◽  
Axel Stadie ◽  
Eike Schwandt ◽  
Robert Reisch ◽  
Cleopatra Charalampaki ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Virtual Reality Environment ◽  
Collaborative Virtual Reality ◽  
Neurosurgical Planning ◽  
And Training

A Collaborative Virtual Reality Environment for Liver Surgery Planning

2021 ◽  
Author(s):  
Vuthea Chheang ◽  
Patrick Saalfeld ◽  
Fabian Joeres ◽  
Christian Boedecker ◽  
Tobias Huber ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Liver Surgery ◽  
Virtual Reality Environment ◽  
Surgery Planning ◽  
Collaborative Virtual Reality

scholarly journals WONKAandOOMMPPAA: analysis of protein–ligand interaction data to direct structure-based drug design

2017 ◽  
Vol 73 (3) ◽  
pp. 279-285
Author(s):  
Charlotte M. Deane ◽  
Ian D. Wall ◽  
Darren V. S. Green ◽  
Brian D. Marsden ◽  
Anthony R. Bradley
Keyword(s):  
Three Dimensional ◽  
Structural Data ◽  
Data Sets ◽  
Interaction Data ◽  
Activity Data ◽  
Ligand Interaction ◽  
Structure Based Drug Design ◽  
Web Based ◽  
Protein Ligand Interaction ◽  
Ligand Activity

In this work, two freely available web-based interactive computational tools that facilitate the analysis and interpretation of protein–ligand interaction data are described. Firstly,WONKA, which assists in uncovering interesting and unusual features (for example residue motions) within ensembles of protein–ligand structures and enables the facile sharing of observations between scientists. Secondly,OOMMPPAA, which incorporates protein–ligand activity data with protein–ligand structural data using three-dimensional matched molecular pairs.OOMMPPAAhighlights nuanced structure–activity relationships (SAR) and summarizes available protein–ligand activity data in the protein context. In this paper, the background that led to the development of both tools is described. Their implementation is outlined and their utility using in-house Structural Genomics Consortium (SGC) data sets and openly available data from the PDB and ChEMBL is described. Both tools are freely available to use and download at http://wonka.sgc.ox.ac.uk/WONKA/ and http://oommppaa.sgc.ox.ac.uk/OOMMPPAA/.

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