HIGH PERFORMANCE BIOMEDICAL COMPUTING
高性能生物医学计算
基本信息
- 批准号:3774957
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:
- 资助国家:美国
- 起止时间:至
- 项目状态:未结题
- 来源:
- 关键词:X ray crystallography computer assisted sequence analysis computer center computer data analysis computer program /software computer simulation computer system design /evaluation computer system hardware electron microscopy image processing linkage mapping mathematical model model design /development molecular dynamics nuclear magnetic resonance spectroscopy parallel processing protein folding protein sequence quantum chemistry radiation therapy dosage
项目摘要
The goals of the high performance biomedical computing program are to
identify and solve those computational problems in biomedicine that can
benefit from high performance hardware, modern software engineering
principles, and efficient algorithms. This effort includes providing
high performance parallel computer systems for the NIH staff and
developing parallel algorithms for biomedical applications.
CBEL is developing algorithms for a number of biomedical applications
that can benefit from computational speedup including image processing
of electron micrographs, protein and nucleic acid sequence analysis,
nuclear magnetic resonance spectroscopy, x-ray crystallography, protein
folding prediction, quantum chemical methods, molecular dynamics
simulations, human genetic linkage analysis, medical imaging, and
radiation treatment planning. Developing teams for each application area
include computer engineers and scientists from CBEL who design and
implement the required parallel algorithms and methods, and biomedical
scientists who provide the necessary application knowledge and become
users of the developed software. The ultimate goal is to have high
performance parallel computing facilitate the science that is done at
NIH. While developing these computationally demanding applications, CBEL
is investigating the following high performance computing issues:
partitioning a problem into many parts that can be independently executed
on different processors, designing algorithms so that delays of
interprocessor communication can be kept to a small fraction of the
computation time, designing the parts so that the computing load can be
distributed evenly over the available processors or dynamically balanced,
designing algorithms so that the number of processors is a parameter and
the algorithms can be configured dynamically for the available machine,
developing tools and environments for producing portable parallel
programs and monitoring system performance, and proving that a parallel
algorithm on a given machine meets its specifications.
The work of CBEL staff has contributed to a number of findings of
biomedical significance in the past year. Working with NIAMS
collaborators, progress was made on determining the three-dimensional
location of the major capsid proteins of the herpes simplex virus (type
1). NIDDK has used parallel computing methods to improve their procedure
for determining the structure of the protein Calmodulin from NMR spectra
data. Another group of scientists from NIDDK simulated the kinetics of
nitric oxide rebinding to myoglobin following photodissociation on the
CBEL parallel computer. NIMH investigators used parallel image
registration techniques developed by CBEL staff to study the progression
of Alzheimer's disease from PET images of the brain. High performance
computing has allowed NEI researchers to determine the onset time, the
rate of information encoding, and the total amount of information encoded
by the neuronal responses to different parameters of a visual stimulus
in primates.
高性能生物医学计算程序的目标是
识别和解决生物医学中的计算问题,
得益于高性能硬件、现代软件工程
原则和高效算法。 这项工作包括提供
为NIH工作人员提供高性能并行计算机系统,
为生物医学应用开发并行算法。
CBEL正在为许多生物医学应用开发算法
可以从包括图像处理在内的计算加速中受益
电子显微照片,蛋白质和核酸序列分析,
核磁共振波谱,x射线晶体学,蛋白质
折叠预测,量子化学方法,分子动力学
模拟,人类遗传连锁分析,医学成像,以及
放射治疗计划 为每个应用领域开发团队
包括CBEL的计算机工程师和科学家,他们设计并
实现所需的并行算法和方法,
科学家谁提供必要的应用知识,并成为
开发软件的用户。 最终目标是要有高
性能并行计算促进了在
国家卫生研究院 在开发这些计算要求很高的应用程序时,CBEL
正在调查以下高性能计算问题:
将问题划分为许多可以独立执行的部分
在不同的处理器上,设计算法,
处理器间通信可以保持在
计算时间,设计部件,以便计算负载可以
均匀地分布在可用的处理器上或动态地平衡,
设计算法,使得处理器的数量是参数,以及
可以为可用机器动态地配置算法,
开发用于产生可移植并行的工具和环境
程序和监控系统的性能,并证明了一个并行
给定机器上的算法符合其规范。
CBEL工作人员的工作促成了一些调查结果,
在过去的一年里,生物医学的重要性。 与NIAMS合作
合作者,在确定三维
单纯疱疹病毒主要衣壳蛋白的位置(型
1)。 NIDDK已经使用并行计算方法来改进他们的程序
用于从NMR光谱确定蛋白质钙调素的结构
数据 NIDDK的另一组科学家模拟了
一氧化氮再结合肌红蛋白后,光解离的
CBEL并行计算机。 NIMH研究人员使用平行图像
CBEL工作人员开发的注册技术,用于研究进展
阿尔茨海默病的大脑PET图像。 高性能
计算使NEI研究人员能够确定发病时间,
信息编码的速率和编码的信息总量
通过神经元对视觉刺激的不同参数的反应
在灵长类动物中。
项目成果
期刊论文数量(0)
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