代谢组学
范围(计算机科学)
数据科学
生化工程
计算生物学
计算机科学
工程伦理学
生物技术
生物
管理科学
工程类
生物信息学
程序设计语言
作者
Xin Meng,Yan Liu,SHUJUN XU,LIANRONG YANG,RUI YIN
出处
期刊:Biocell
日期:2024-01-01
卷期号:48 (1): 65-78
被引量:1
标识
DOI:10.32604/biocell.2023.045986
摘要
Over the past decade, the swift advancement of metabolomics can be credited to significant progress in technologies such as mass spectrometry, nuclear magnetic resonance, and multivariate statistics. Currently, metabolomics garners widespread application across diverse fields including drug research and development, early disease detection, toxicology, food and nutrition science, biology, prescription, and chinmedomics, among others. Metabolomics serves as an effective characterization technique, offering insights into physiological process alterations in vivo. These changes may result from various exogenous factors like environmental conditions, stress, medications, as well as endogenous elements including genetic and protein-based influences. The potential scientific outcomes gleaned from these insights have catalyzed the formulation of innovative methods, poised to further broaden the scope of this domain. Today, metabolomics has evolved into a valuable and widely accepted instrument in the life sciences. However, comprehensive reviews focusing on the sample preparation and analytical methodologies employed in metabolomics within the life sciences are surprisingly scant. This review aims to fill that gap, providing an overview of current trends and recent advancements in metabolomics. Particular emphasis is placed on sample preparation, sophisticated analytical techniques, and their applications in life science research.
科研通智能强力驱动
Strongly Powered by AbleSci AI