Advance of Peptide Detectability Prediction on Mass Spectrometry Platform in Proteomics
10.3724/SP.J.1096.2010.00286
- VernacularTitle:蛋白质组学质谱平台肽段可检测性预测研究进展
- Author:
Changming XU
;
Jiyang ZHANG
;
Hui LIU
;
Hanchang SUN
;
Yunping ZHU
;
Hongwei XIE
- Publication Type:Journal Article
- Keywords:
Biological mass spectrometry;
Proteomics;
Peptide detectability;
Machine learning;
Review
- From:
Chinese Journal of Analytical Chemistry
2010;38(2):286-292
- CountryChina
- Language:Chinese
-
Abstract:
As the complexity of samples and experimental processes, the repeatability of mass spectrometry experiments is still not satisfactory, the results of peptide identification and quantification show high randomicity), the probability of peptide being detected by mass spectrometry in proteome research, especially in quantitative proteomic study, has received much attention. Therefore, a lot of experimental researches have been done, as well as a number of computational prediction methods have been developed. In this article, we summarized the important factors impacting the peptide detectability, investigated the existing prediction methods) and reviewed their applications in experimental study.
