糖组学和糖蛋白质组学中的生物信息学协议。
Bioinformatics protocols in glycomics and glycoproteomics.
作者信息
Tang Haixu, Mayampurath Anoop, Yu Chuan-Yih, Mechref Yehia
机构信息
School of Informatics and Computing, Indiana University, Bloomington, Indiana.
Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas.
出版信息
Curr Protoc Protein Sci. 2014 Apr 1;76:2.15.1-2.15.7. doi: 10.1002/0471140864.ps0215s76.
Glycomics aims to identify the whole set of functional glycans of glycoconjugates (attached to proteins or lipids) in biological samples. Glycoproteomics aims to characterize the complete structure of all glycoproteins in biological samples, including the glycosylation sites of proteins and the various glycan structures attached to each of these sites. Mass spectrometry (MS) and microarray are high-throughput technologies that are commonly used in glycomics and glycoproteomics, which often result in the generation of large experimental datasets. Bioinformatics approaches play an essential role in automated analysis and interpretation of such data. This unit describes and discusses the computational tools currently available for these analyses, and their glycomics and glycoproteomics applications.
糖组学旨在鉴定生物样品中糖缀合物（与蛋白质或脂质相连）的全套功能性聚糖。糖蛋白质组学旨在表征生物样品中所有糖蛋白的完整结构，包括蛋白质的糖基化位点以及连接到每个这些位点的各种聚糖结构。质谱（MS）和微阵列是糖组学和糖蛋白质组学中常用的高通量技术，这通常会产生大量的实验数据集。生物信息学方法在这些数据的自动分析和解释中起着至关重要的作用。本单元描述并讨论了目前可用于这些分析的计算工具及其在糖组学和糖蛋白质组学中的应用。
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