Aoki-Kinoshita Kiyoko F
Department of Bioinformatics, Faculty of Engineering, Soka University, 1-236 Tangi-machi, Hachioji, Tokyo, 192-8577, Japan,
Methods Mol Biol. 2015;1273:193-202. doi: 10.1007/978-1-4939-2343-4_14.
This chapter describes the ProfilePSTMM Tool, which is available as a part of the RINGS (Resource for INformatics of Glycomes at Soka) website. It implements the probabilistic model previously described by Aoki-Kinoshita et al. (Bioinformatics 22:e25-e34, 2006). This tool computes the glycan patterns that are found within a given set of glycan structures. Thus, one application of this tool is the extraction of monosaccharide patterns (profile) of a set of glycans that bind to a particular glycan-binding protein. Such patterns could be regarded as the monosaccharides that are important for glycan recognition. The resulting profiles are displayed similarly to Sequence Logos for amino acid motifs, where for each position in the glycan, the statistical distribution of monosaccharides that are found at that position are displayed graphically. An example of the analysis of Siglec-7 is described.
本章介绍了ProfilePSTMM工具,它是作为RINGS(创价大学糖组信息资源)网站的一部分提供的。它实现了青木木下等人(《生物信息学》22:e25 - e34,2006年)先前描述的概率模型。该工具计算给定一组聚糖结构中发现的聚糖模式。因此,该工具的一个应用是提取与特定聚糖结合蛋白结合的一组聚糖的单糖模式(概况)。这种模式可被视为对聚糖识别很重要的单糖。所得的概况显示方式类似于氨基酸基序的序列标识,其中对于聚糖中的每个位置,该位置发现的单糖的统计分布以图形方式显示。文中描述了对Siglec - 7的分析示例。