Physico-Chimie Curie, Institut Curie, PSL Research University, CNRS UMR 168, F-75005, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, CNRS UMR 168, F-75005, Paris, France.
Decision and Bayesian Computation, Institut Pasteur, CNRS UMR 3571, Paris, France; Center for Biostatistics, Bioinformatics and Integrative Biology (C3BI), Institut Pasteur, USR 3756 IP CNRS, Paris, France.
J Mol Biol. 2019 Mar 29;431(7):1315-1321. doi: 10.1016/j.jmb.2019.01.033. Epub 2019 Feb 7.
Virtual reality (VR) has recently become an affordable technology. A wide range of options are available to access this unique visualization medium, from simple cardboard inserts for smartphones to truly advanced headsets tracked by external sensors. While it is now possible for any research team to gain access to VR, we can still question what it brings to scientific research. Visualization and the ability to navigate complex three-dimensional data are undoubtedly a gateway to many scientific applications; however, we are convinced that data treatment and numerical simulations, especially those mixing interactions with data, human cognition, and automated algorithms will be the future of VR in scientific research. Moreover, VR might soon merit the same level of attention to imaging data as machine learning currently has. In this short perspective, we discuss approaches that employ VR in scientific research based on some concrete examples.
虚拟现实（VR）技术最近变得经济实惠。现在有很多种方法可以访问这种独特的可视化媒介，从简单的智能手机用纸板插入式到真正先进的外部传感器跟踪式头显都有。虽然现在任何研究团队都可以获得 VR，但我们仍然可以质疑它为科学研究带来了什么。可视化和导航复杂三维数据的能力无疑是许多科学应用的门户；然而，我们坚信数据处理和数值模拟，特别是那些混合了数据交互、人类认知和自动化算法的应用，将是 VR 在科学研究中的未来。此外，VR 可能很快就会像机器学习目前对成像数据一样受到关注。在这篇短评中，我们将根据一些具体例子来讨论在科学研究中使用 VR 的方法。
