摘要
模式识别(PR)是把具体事物进行正确归类的科学, 它能解决许多对复杂体系的认识问题. 生物医学核磁共振波谱(NMR)的理解和分析便是其中一种. 在受到病理或者其他刺激后, 生物体内的代谢物水平会发生变化, 这种变化可以通过液体高分辨核磁共振的手段来观察. 模式识别把这种认识进一步深化, 不仅可以将正常状态与病理状态区分开, 还能找到是哪些生化指纹导致两种状态的差异, 为生理、病理和药理等研究, 以及临床诊断提供依据. 模式识别与生物核磁共振波谱的结合, 已经发展成为代谢组学研究的关键技术, 甚至被称为基于核磁共振的代谢组学. 主要讨论适用于生物医学核磁共振中的模式识别方法及其最新进展.
Pattern recognition (PR) is the technology of making a decision on a concrete object which category it belongs to PR can be used to solve many problems in understanding complex systems One of its applications is the comprehension and analysis of biomedical magnetic resonance spectroscopy data Previous studies using high-resolution liquid NMR spectroscopy have shown that the levels of metabolites in biological samples change with the time after pathological or other perturbation PR can be used not only to identify the differences of the pathological from the normal, but also to find which bio-fingerprints result in such differences, thus supplying valuable information for diagnosis In this review, various statistical PR methods used in biomedical magnetic resonance spectroscopy are discussed, and the latest progresses in this field are introduced
出处
《波谱学杂志》
CAS
CSCD
北大核心
2005年第1期99-111,共13页
Chinese Journal of Magnetic Resonance
基金
国家自然科学基金(10234070
20475061)
"973"(2002CB713806)和CAS(KJCX2 SW 03)资助项目.
关键词
生物医学
核磁共振波谱
病理状态
代谢组学
正常状态
PR
药理
复杂体系
正确
NMR
biomedical magnetic resonance, high-resolution nuclear magnetic resonance (HR-NMR), pattern recognition (PR), multivariate statistics, metabonomics