Autostereoscopic Visualization and Geometric Computing for Biological Macromolecules

生物大分子的自动立体可视化和几何计算

• 批准号: 0429753
• 负责人: Amitabh Varshney
• 金额: $ 23万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0429753&HistoricalAwards=false
• 关键词: Autostereoscopic; Visualization; Geometric; Computing; Biological

NSF 0429753 Autostereoscopic Visualization and Geometric Computing forBiological MacromoleculesThe planned research seeks to develop tools and techniques forvisualization and geometric reasoning for large proteomics data. Theproposed research has three main components -- implicit-function-basedrepresentations for proteins, faster computation of proteinelectrostatics, and real-time auto-stereoscopic visualization. Theresearch will develop a unified framework of implicit functions thatcan compactly and efficiently represent non-bonded protein propertiesincluding protein electrostatics and accessibility. By tightly couplingthese properties, implicit-function-based representations will likelyresult in synergistically favorable crossovers in the solutions to theseproblems. Further, providing adaptive, progressive, and hierarchicalrepresentations for implicit functions will allow them to be used inmultiresolution schemes for storage, transmission, and computationalsteering. Protein electrostatic interactions are of central importance formany biological processes. Autostereoscopic visualization of proteinsand their properties is important in understanding the 3D structure ofproteins. The proposed research will develop new methods for renderingimplicit surfaces and volumes using the recent advances in graphicshardware as well as adapt efficient methods for autostereoscopic displayswith personalization.

NSF 0429753自动镜可视化和几何计算，即生物学巨质量计划的研究旨在开发大型蛋白质组学数据的工具和技术。该计划的研究具有三个主要组成部分 - 基于隐式功能的蛋白质表述，蛋白质电位的更快计算以及实时自动示例可视化。 Theresearch将开发一个统一的隐式功能框架，可以紧凑，有效地表示包括蛋白质静电和可访问性的非粘结蛋白质。通过紧密耦合这些属性，基于隐式功能的表示形式可能会在解决方案的解决方案中具有协同有利的分频器。此外，为隐式功能提供自适应，渐进式和层次陈述将使它们被用于存储，传输和计算稳定方案。蛋白质静电相互作用是核心生物学过程的核心重要性。 蛋白质和它们的特性的自动镜可视化对于理解蛋白质的3D结构很重要。拟议的研究将使用GraphicsHardware的最新进展以及适应自动镜显示器显示具有个性化的自动镜显示的新方法来开发用于渲染图表和卷的新方法。