生物信息学应用于代谢物组学研究的进展

Progress and perspective in application of bio-informatics to metabolomics and metabonomics

如何利用代谢物组的海量数据和信息,与其他领域整合并重构完整的生化网络,建立预测细胞表型、优化生化过程和评价药物安全性的崭新方法是生物信息学需要解决的重要问题.本文综述了代谢物组数据分析中应用的主要生物信息学方法及关键问题,列举了各种方法在植物、微生物及哺乳动物体系的重要应用.最后对代谢物组学的前景进行展望.

One of the challenges of contemporary bio-informatics is how to utilize the huge volume of data and information from high throughput metabolomics and metabonomics studies for reconstructing biochemical network, predicting cell phenotype, optimizing bio-process and evaluating drug safety with novel methods. This paper briefly reviews major methods including supervised as well as unsupervised methods and highlights key issues of bio-informatics analysis within metabolomics and metabolomics research such as extracting and pre-processing data, establishing data standards and integrating with relevant research fields such as genomics, transcriptomics and proteomics. Several important applications in plant, microorganism and mammalian systems are also included and the paper ends up with a prospect of the new ‘omics＇.