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The VRNetzer platform enables interactive network analysis in Virtual Reality
Networks provide a powerful representation of interacting components within complex systems, making them ideal for visually and analytically exploring big data. However, the size and complexity of many networks render static visualizations on typically-sized paper or screens impractical, resulting i...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8065164/ https://www.ncbi.nlm.nih.gov/pubmed/33893283 http://dx.doi.org/10.1038/s41467-021-22570-w |
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author | Pirch, Sebastian Müller, Felix Iofinova, Eugenia Pazmandi, Julia Hütter, Christiane V. R. Chiettini, Martin Sin, Celine Boztug, Kaan Podkosova, Iana Kaufmann, Hannes Menche, Jörg |
author_facet | Pirch, Sebastian Müller, Felix Iofinova, Eugenia Pazmandi, Julia Hütter, Christiane V. R. Chiettini, Martin Sin, Celine Boztug, Kaan Podkosova, Iana Kaufmann, Hannes Menche, Jörg |
author_sort | Pirch, Sebastian |
collection | PubMed |
description | Networks provide a powerful representation of interacting components within complex systems, making them ideal for visually and analytically exploring big data. However, the size and complexity of many networks render static visualizations on typically-sized paper or screens impractical, resulting in proverbial ‘hairballs’. Here, we introduce a Virtual Reality (VR) platform that overcomes these limitations by facilitating the thorough visual, and interactive, exploration of large networks. Our platform allows maximal customization and extendibility, through the import of custom code for data analysis, integration of external databases, and design of arbitrary user interface elements, among other features. As a proof of concept, we show how our platform can be used to interactively explore genome-scale molecular networks to identify genes associated with rare diseases and understand how they might contribute to disease development. Our platform represents a general purpose, VR-based data exploration platform for large and diverse data types by providing an interface that facilitates the interaction between human intuition and state-of-the-art analysis methods. |
format | Online Article Text |
id | pubmed-8065164 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-80651642021-05-11 The VRNetzer platform enables interactive network analysis in Virtual Reality Pirch, Sebastian Müller, Felix Iofinova, Eugenia Pazmandi, Julia Hütter, Christiane V. R. Chiettini, Martin Sin, Celine Boztug, Kaan Podkosova, Iana Kaufmann, Hannes Menche, Jörg Nat Commun Article Networks provide a powerful representation of interacting components within complex systems, making them ideal for visually and analytically exploring big data. However, the size and complexity of many networks render static visualizations on typically-sized paper or screens impractical, resulting in proverbial ‘hairballs’. Here, we introduce a Virtual Reality (VR) platform that overcomes these limitations by facilitating the thorough visual, and interactive, exploration of large networks. Our platform allows maximal customization and extendibility, through the import of custom code for data analysis, integration of external databases, and design of arbitrary user interface elements, among other features. As a proof of concept, we show how our platform can be used to interactively explore genome-scale molecular networks to identify genes associated with rare diseases and understand how they might contribute to disease development. Our platform represents a general purpose, VR-based data exploration platform for large and diverse data types by providing an interface that facilitates the interaction between human intuition and state-of-the-art analysis methods. Nature Publishing Group UK 2021-04-23 /pmc/articles/PMC8065164/ /pubmed/33893283 http://dx.doi.org/10.1038/s41467-021-22570-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Pirch, Sebastian Müller, Felix Iofinova, Eugenia Pazmandi, Julia Hütter, Christiane V. R. Chiettini, Martin Sin, Celine Boztug, Kaan Podkosova, Iana Kaufmann, Hannes Menche, Jörg The VRNetzer platform enables interactive network analysis in Virtual Reality |
title | The VRNetzer platform enables interactive network analysis in Virtual Reality |
title_full | The VRNetzer platform enables interactive network analysis in Virtual Reality |
title_fullStr | The VRNetzer platform enables interactive network analysis in Virtual Reality |
title_full_unstemmed | The VRNetzer platform enables interactive network analysis in Virtual Reality |
title_short | The VRNetzer platform enables interactive network analysis in Virtual Reality |
title_sort | vrnetzer platform enables interactive network analysis in virtual reality |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8065164/ https://www.ncbi.nlm.nih.gov/pubmed/33893283 http://dx.doi.org/10.1038/s41467-021-22570-w |
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