Database-centric data analysis of molecular simulations

以数据库为中心的分子模拟数据分析

• 批准号: 8259152
• 负责人: Yicheng Tu
• 金额: $ 17.33万
• 依托单位: UNIVERSITY OF SOUTH FLORIDA
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-04-15 至 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8259152
• 关键词: Algorithms; Applications Grants; Biochemical Process; Biomedical Research; Biophysical Process; Collagen Fibril; Communities; Complex; Computer software; Computers; Data; Data Analyses; Data Base Management; Data Compression; Data Security; Data Set; Data Storage and Retrieval; Database Management Systems; Databases; Dependency; Development; Diagnosis; Disease; Ensure; Environment; Event; Feedback; Free Energy; Goals; Hereditary Disease; Informatics; Language; Maintenance; Medical Research; Medicine; Memory; Metadata; Methods; Modeling; Modification; Molecular; Molecular Biology; Monitor; Monte Carlo Method; Names; Nature; Output; Pathology; Performance; Pharmaceutical Preparations; Policies; Positioning Attribute; Process; Reaction; Reading; Research; Research Personnel; Research Project Grants; Resort; Retrieval; Running; Scheme; Scientist; Security; Site; Solutions; Source; Speed; Structure; System; Techniques; Technology; Testing; Thermodynamics; Time; Work; active control; analytical tool; base; computerized data processing; data integrity; data reduction; database design; design; falls; improved; indexing; information processing; innovation; molecular dynamics; molecular scale; nano; novel; process optimization; programs; simulation; simulation software; software systems; structural biology; success

DESCRIPTION (provided by applicant): Molecular simulations (MS) have become an integral part of molecular and structural biology. By pro- viding model descriptions for biochemical and biophysical processes at nano-scopic scale, MS can provide fundamental understanding of diseases and help discovery of drugs. MS, by their nature, generate large amounts of data. Although many of the MS software are carefully designed to achieve maximum computational performance in simulation, they seriously fall short on storage and handling of the large scale data output. The objective of the proposed research is to use database technologies to improve the efficiency, ease of maintenance, and security of MS data analysis. We propose to accomplish this by developing novel data structures and query processing algorithms in the kernel of the database management system (DBMS), in addition to leveraging the advantages of such systems in their current forms. Based on the success of above database-centric techniques, we will also develop automatic feedback control mechanisms in MS to improve the online tuning of simulations that is needed in studying many biochemical processes. The project has three specific aims: 7 Development of a Database-centric MS (DCMS) data analysis framework that stores simulation data collected from various sources, provides standard application programming interfaces (APIs) for data retrieval, and allows global data access to research community while ensuring fine data security policies. 7 Augmenting DCMS with novel data structures and algorithms for efficient data retrieval and query processing. We focus on creative indexing and data organization techniques, and query processing and optimization strategies. 7 Integration of DCMS and steering-based MS programs into one unified simulation framework that can greatly improve the efficiency of the MS process. This framework will be demonstrated as part of the efforts to solve real biomedical problems. We believe DCMS will produce a revolutionary high throughput technique for MS researchers and accelerate the discovery process in medical research. Such innovations will bring significant intellectual merit from which both the biomedical and database management communities will benefit.

描述（由申请人提供）：分子模拟（MS）已成为分子和结构生物学的一个组成部分。通过提供纳米级生化和生物物理过程的模型描述，MS 可以提供对疾病的基本了解并帮助发现药物。就其本质而言，MS 会生成大量数据。尽管许多MS软件都经过精心设计，以在模拟中实现最大的计算性能，但它们在大规模数据输出的存储和处理方面严重不足。本研究的目标是使用数据库技术来提高 MS 数据分析的效率、易于维护性和安全性。我们建议通过在数据库管理系统（DBMS）的内核中开发新颖的数据结构和查询处理算法来实现这一目标，此外还利用此类系统当前形式的优势。基于上述以数据库为中心的技术的成功，我们还将开发 MS 中的自动反馈控制机制，以改进研究许多生化过程所需的模拟在线调整。该项目有三个具体目标： 7 开发以数据库为中心的 MS (DCMS) 数据分析框架，存储从各种来源收集的模拟数据，提供用于数据检索的标准应用程序编程接口 (API)，并允许研究社区访问全球数据，同时确保良好的数据安全策略。 7 使用新颖的数据结构和算法增强 DCMS，以实现高效的数据检索和查询处理。我们专注于创造性的索引和数据组织技术，以及查询处理和优化策略。 7 将 DCMS 和基于转向的 MS 程序集成到一个统一的仿真框架中，可以大大提高 MS 过程的效率。该框架将作为解决实际生物医学问题的努力的一部分进行展示。我们相信 DCMS 将为 MS 研究人员带来革命性的高通量技术，并加速医学研究的发现过程。这些创新将带来重大的智力成果，生物医学和数据库管理界都将从中受益。