Virtual reality in bioinformatics

Pritee Chunarkar Patil, Tanisha Batra
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引用次数: 3

Abstract

Virtual reality (VR) is an influencing cyberknowledge subject, occurring within an imitated environment that integrates mainly auditory and visual, but also additional kinds of sensory feedbacks. Virtual Reality linked topics play a main role in several research areas. Bioinformatics generally deals with biological macromolecules, the nominal creatures of existence; thus, visualization displays a main part in the study. The use of stereoscopic interpretation has remained for an extended time for envisioning molecular structures, coming reverse for the former buildup of VR equipment’s was done before the CAVE was designed and Head-Mounted Displays (HMD) were available at a reasonable price. Generated by the accomplishment of novel, current HMDs like Oculus Rift as well as HTC Vive, Virtual Reality contains lately regained countless interest. Contrarily, a novel manufacture of significant “computational microscopes” has been recognized, for instance the CAVE2, producing outsized, just about 360 degree-spanning visualization services. Furthermore, in the earlier period these approaches were restricted to cost-intensive proficient visualization services. The arrival of fresh reasonably priced, and frequent mobile technologies, provides elevated probable for using related approaches on a regular basis for every day research. Visual Analytics is productively being used for numerous years to examine complex and heterogeneous datasets. Immersive Analytics combines these approaches now with new immersive and interactive technologies.1–3
生物信息学中的虚拟现实
虚拟现实(VR)是一门影响网络知识的学科,它发生在一个模拟的环境中,主要集成了听觉和视觉,但也有其他类型的感官反馈。虚拟现实相关课题在多个研究领域发挥着重要作用。生物信息学一般处理生物大分子,名义上的生物存在;因此,可视化在研究中占有重要的地位。立体解释的使用已经持续了很长一段时间,用于想象分子结构,而在CAVE设计和头戴式显示器(HMD)以合理的价格可用之前,VR设备的构建已经完成。由于Oculus Rift和HTC Vive等新颖的头戴式设备的成功,虚拟现实最近重新获得了无数的兴趣。相反,一种重要的“计算显微镜”的新制造已经被认可,例如CAVE2,可以产生超大的,大约360度的可视化服务。此外,在早期,这些方法仅限于成本密集的精通可视化服务。新的、价格合理的、频繁的移动技术的出现,为日常研究定期使用相关方法提供了更高的可能性。多年来,可视化分析被有效地用于检查复杂和异构的数据集。现在,沉浸式分析将这些方法与新的沉浸式和交互式技术相结合
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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