Database-centric data analysis of molecular simulations

描述(申请人提供)：分子模拟(MS)已成为分子和结构生物学不可或缺的一部分。通过在纳米尺度上提供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，并有助于药物的发现。多发性硬化症本质上会产生大量数据。尽管许多MS软件经过精心设计以在模拟中实现最大的计算性能，但它们在存储和处理大规模数据输出方面严重不足。建议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)的内核中开发新的数据结构和查询处理算法来实现这一点，此外还利用这些系统目前形式的优势。基于上述以数据库为中心的技术的成功，我们还将在MS中开发自动反馈控制机制，以改进研究许多生化过程所需的模拟的在线调整。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)，并允许研究界访问全球数据，同时确保良好的数据安全政策。7使用新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。这一框架将作为解决实际生物医学问题的努力的一部分进行演示。我们相信，DCMS将为MS研究人员提供一种革命性的高通量技术，并加快医学研究的发现进程。这种创新将带来重大的智力价值，生物医学和数据库管理界都将从中受益。

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.