Virtual Reality (VR), Mixed Reality (MR) and Augmented Reality (AR) are technologies that have been around for many years. However, only in the last few years with falling costs and increasingly powerful headsets, have they started to become useful tools in the medical sciences that can impact disease understanding and patient wellbeing at many levels. The umbrella term for these modalities is extended Reality (XR).
There are a wide range of potential applications of XR in bioinformatics for data interrogation and visualization. These techniques offer potential to improve the efficiency of interacting with complex biological data sets, ultimately giving insight to analysis that desktop based systems cannot achieve.
We welcome submissions of original research and reviews on (but not limited) to the following topics:
3D Imaging Research and Clinical Image Visualisation
• Analysis of 3D biomedical imaging data from all modalities
• Surgical planning and visualisation
• Using XR combined with computer vision and artificial intelligence
Transcriptomics, Proteomics and Epigenetics
• Single cell data analysis
• 3D genome analysis
• Spatial transcriptomics
Protein Structure
• Viewing and interreacting with protein molecules
• Interacting with protein complexes
• Improving docking
We are especially interested in single-cell, genome, spatial omics and ecosystem science related techniques but will accept papers from other areas when appropriate.
Virtual Reality (VR), Mixed Reality (MR) and Augmented Reality (AR) are technologies that have been around for many years. However, only in the last few years with falling costs and increasingly powerful headsets, have they started to become useful tools in the medical sciences that can impact disease understanding and patient wellbeing at many levels. The umbrella term for these modalities is extended Reality (XR).
There are a wide range of potential applications of XR in bioinformatics for data interrogation and visualization. These techniques offer potential to improve the efficiency of interacting with complex biological data sets, ultimately giving insight to analysis that desktop based systems cannot achieve.
We welcome submissions of original research and reviews on (but not limited) to the following topics:
3D Imaging Research and Clinical Image Visualisation
• Analysis of 3D biomedical imaging data from all modalities
• Surgical planning and visualisation
• Using XR combined with computer vision and artificial intelligence
Transcriptomics, Proteomics and Epigenetics
• Single cell data analysis
• 3D genome analysis
• Spatial transcriptomics
Protein Structure
• Viewing and interreacting with protein molecules
• Interacting with protein complexes
• Improving docking
We are especially interested in single-cell, genome, spatial omics and ecosystem science related techniques but will accept papers from other areas when appropriate.
